Advanced Studies Programs
Department of Electronics and Computer Engineering
Master of Engineering in Electronics & Communications Engineering (M.Eng ECE)
| Course Requirements | |
| Foundation subjects | 12 units |
| Methods of Research | 3 units |
| Advanced Mathematics | 6 units |
| Major subjects | 15 units |
| Cognates / electives | 6 units |
| Practicum | 6 units |
| Orientation for Non-DLSU graduates | (1 unit) |
| Total | 48 units |
Note: The foundation courses that a student should take may be reduced or waived; however, the student has to complete the 48-units requirement by taking more elective subjects as substitute to the foundation courses.
Master of Science in Electronics & Communication Engineering (M.S. ECE.)
| Course Requirements | |
| Methods of Research | 3 units |
| Advanced Mathematics | 6 units |
| Major subjects | 15 units |
| Cognates / electives | 6 units |
| Thesis | 6 units |
| Orientation for Non-DLSU graduates | (1 unit) |
| Total | 36 units |
Note: Cognates/Electives may be chosen from other engineering graduate programs.
Doctor of Philosophy in Electronics & Communications Engineering (Ph.D ECE)
| Course requirements | |
| Specialization Courses | 12 units |
| Philosophy course | 3 units |
| Seminar | 3 units |
| Dissertation | 12 units |
| Orientation for Non-DLSU graduates | (1 unit) |
| Total | 30 units |
Required Courses
| A. Foundation Courses (required 12 units for M. Eng) | ||
| COURSE CODE | COURSE TITLE | DESCRIPTION |
| COE5010 | Engineering Mathematics | This course covers Review of First-order-First-degree differential equation, Laplace Transforms, Systems of linear differential equation with constant coefficients, Power Series Solution of Differential Equations, Fourier Series, and Partial Differential Equations. |
| COE5020 | Quantitative Methods | The course covers the basic concepts of probability, random variables, special discrete and continuous probability distributions, sampling concepts, sampling distributions, hypothesis testing, and linear regression and correlation analysis. |
| COE5410 | Computer Engineering | This course covers topics on variables, constants, operations and expressions, program control statements, functions, arrays, structures, unions, I/O disk files, understanding memory models, turbo-C. |
| COE571M | Techpreneurship | This course takes the participant through entrepreneurship in technology ventures, which is about commercializing technology ideas into viable enterprises. It is about training techies, scientists and researchers in the skills and attitudes of entrepreneurs, about empowering them to realize the opportunities and commercial values arising from their ideas, technologies, technology applications or products. The course examines the development of ideas and how these are translated into opportunities and eventually businesses; it challenges the students to go through the process of writing a business plan, which will be their final output in this course. |
| B. Orientation (1 unit, Non-Academic) | ||
| COE5000 | Engineering Orientation | The course includes topics on the DLSU history, mission statement, organizational structure, key officers/offices; the Brothers of the Christian Schools, the life and writings of St. John Baptist de la Salle; Lasallian core values and professional ethics. |
| C. Basic Subject (3 units Required) | ||
| COE5200 | Methods of Research | A study of the fundamentals of research designs, analysis and interpretations of data, project feasibility studies, and qualitative research techniques |
| COE559D | Philosophy of Technology (for PhD students only) | The course provides a focal point for the creators and doers of technology to examine critically and reflect upon the social influences of technology. The course discusses the philosophical foundation of science, technology, and engineering and analyzes their relationship. It includes a brief presentation of the history of science, technology and engineering surveying major developments from the Industrial Revolution to the present and introduces ethical issues in the work life of engineers and scientists. |
| D. Advanced Mathematics (6 units Required) | ||
| COE5310 | Advanced Mathematical Methods | Review of linear algebra and linear differential equation, existence and uniqueness, autonomous systems, phase portraits, nonlinear system, linearization, stability, perturbation, chaos and bifurcation. |
| COE5320 | Numerical Methods with Computer Programming and Application | Matrix computations, roots of linear and non-linear system, interpolation, numerical integration and differentiation, predictor connector, and Runge Kutta Methods, finite difference methods and introduction to finite element methods. |
| COE5100 | Statistical Analysis and Design | Basic Research Methods; analysis of variance and convariance; Experimental Design; Advanced Regression Analysis; Non-Parametric Test |
COURSE CODE |
COURSE DESCRIPTION |
COURSE TYPE |
COURSE DESCRIPTION |
ECE |
|||
| COE5330 | Advanced Mathematical Methods for ECE | Basic | This course involves mathematical concepts needed in the study of electronics and communications. These include Fourer Series, Laplace. Fouries Z, Hilbert transforms Bescel equations and functions, probabilities and random processes. |
| COE533D | Advanced Mathematical Methods for Ph.D.-ECE | Major | This is an extension of COE 5330 intended for PhD students. This course involves mathematical concepts needed in the study of electronics and comminications. These include Fourer series, Laplace, Fouries Z, and Hilbert transforms; Bescel equations and functions; probabilities and random processes. |
| ECE525M | Digital Integrated Circuit Design | Major | This is a 3 unit course with laboratory component. Topics covered include: MOS Fundamentals, CMOS Circuit Fundamentals, CMOS Inverter and its characteristics, inverter chain, pass transistor logic, ratioed logic, random logic, tally circuit, complex logic, stick diagram, geometric layout and layout rules, dynamic logic, flip flops, precharged logic, domino logic, NORA logic, pipelining, dynamic gate power consumption, combinational logic path optimization, different binary adders, shifters and memory. Electric and Winspice are the tools used for lab sessions which will focused on combinational logic , sequential logic circuit characterization and geometric layouting. |
| ECE525D | Digital Integrated Circuit Design (for PhD) | Major | This is an extension of ECE525M intended for PhD students.This is a 3 unit course with laboratory component. Topics covered include: MOS Fundamentals, CMOS Circuit Fundamentals, CMOS Inverter and its characteristics, inverter chain, pass transistor logic, ratioed logic, random logic, tally circuit, complex logic, stick diagram, geometric layout and layout rules, dynamic logic, flip flops, precharged logic, domino logic, NORA logic, pipelining, dynamic gate power consumption, combinational logic path optimization, different binary adders, shifters and memory. Electric and Winspice are the tools used for lab sessions which will focused on combinational logic , sequential logic circuit characterization and geometric layouting. |
| ECE610M | Data Communications Network Design | Major | This course covers topics in Protocols and basic Principles, multiplexing and design of communication networks, and hierarchical structure. |
| ECE610D | Data Communications Network Design (for Ph.D.) | Major | This is an extension of ECE610M intended for Ph.D. students. Topics included in this subject are: Protocols and basic Principles, multiplexing and design of communication networks, and hierarchical structure. |
| ECE611M | Information Theory and Coding Techniques | Major | Measures of information, probability, statistics application in communication, codings and error correcting codes. |
| ECE611D | Information Theory and Coding Techniques (for Ph.D.) | Major | This is an extension of ECE611M intended for PhD students. This course deals with Measures of information, probability, statistics application in communication, codings and error correcting codes. |
| ECE612M | Radio Wave Propagation and Antenna | Major | This course covers topics on Propagation at different frequencies; Transmission path Loss; rain attenuation; multipath fading; and analysis and design of antenna systems. |
| ECE612D | Radio Wave Propagation and Antenna (for Ph.D) | Major | This is an extension of ECE612M intended for PhD students. It course covers topics on Propagation at different frequencies; Transmission path Loss; rain attenuation; multipath fading; and analysis and design of antenna systems. |
| ECE613M | Applied Instrumentation in Broadcasting | Major | It aims to understand the fundamental engineering principles governing the use of RF and baseband test equipment in terrestrial broadcasting, cable TV and satellite television systems. To perform laboratory exercises that demonstrates standard measurement practices used in the television industry. To gain practical knowledge in the interpretation of data derived from various instruments. |
| ECE613D | Applied Instrumentation in Broadcasting (for Ph.D) | Major | This course is an extension of ECE613M intended for PhD students. It aims to understand the fundamental engineering principles governing the use of RF and baseband test equipment in terrestrial broadcasting, cable TV and satellite television systems. To perform laboratory exercises that demonstrates standard measurement practices used in the television industry. To gain practical knowledge in the interpretation of data derived from various instruments. |
| ECE614M | Microwave Techniques | Major | This course deals with Waveguides Cavity resonators; Passive and active microwave devices; Sparameters and circuit models of active devices; Transformers and coupler; and Mircowave filters. |
| ECE614D | Microwave Techniques (for Ph.D.) | Major | This course is an extension of ECE614M intended for PhD students. It deals with Waveguides Cavity resonators; Passive and active microwave devices; Sparameters and circuit models of active devices; Transformers and coupler; and Mircowave filters. |
| ECE615M | Optical Fiber Communications | Major | The course introduces the principal aspects of fiber optic telecommunications. Providing a brief overview of the history of fiber optics, the course discusses in more detail on the fiber¿s characteristics. The introduction is completed by treating the following system related aspects: sources and detectors, receivers and noise, applications and system components. |
| ECE615D | Optical Fiber Communications (for Ph.D) | Major | This course is an extension of ECE615M intended for PhD students. The course introduces the principle aspects of fiber optic telecommunications. Providing a brief overview of the history of fiber optics, the course discusses in more detail on the fiber¿s characteristics. The introduction is completed by treating the following system related aspects: sources and detectors, receivers and noise, applications and system components. |
| ECE617M | Wireless Communication | Major | This course helps graduate students understand the theoretical and practical aspects of wireless communication systems. The course covers the topics on radiowave propagation, antennas and antenna systems, analysis and design of different wireless communications systems, e.g. satellite communication, microwave system, etc. |
| ECE617D | Wireless Communication (for Ph.D) | Major | This course is an extension of ECE617M intended for PhD students. This subject helps graduate students understand the theoretical and practical aspects of wireless communication systems. The course covers the topics on radiowave propagation, antennas and antenna systems, analysis and design of different wireless communications systems, e.g. satellite communication, microwave system, etc. |
| ECE618M | Advanced Electromagnetic Theory | Major | To make a study of wave phenomenon and detailed treatment of transmission, reflection and refraction of plane waves. Polarization under perpendicular and oblique incidence is also considered in this course. |
| ECE618D | Advanced Electromagnetic Theory (for Ph.D) | Major | This course is an extension of ECE618M intended for PhD students. In this course the students are required to make a study of wave phenomenon and detailed treatment of transmission, reflection and refraction of plane waves. Polarization under perpendicular and oblique incidence is also considered in this course. |
| ECE619M | Network Architecture | Major | This course deals with transmission protocols like TCP/IP and ATM, etc. |
| ECE619D | Network Architecture (for Ph.D) | Major | This course is an extension of ECE619M intended for PhD students. It deals with transmission protocols like TCP/IP, ATM, etc. |
| ECE620M | Neural Networks | Major | This course covers topics on Artificial Neural Networks Concepts and Applications; Supervised, Unsupervised, and Reinforced Learning Architectures; Input/Output Coding Techniques; Adalene and Madalene, Multilayer perception model. BAM and the Hopfeld memory; Counter propagation network, Self-Organizing Map; and Hybrid Neural Network Modeling. |
| ECE620D | Neural Networks (for Ph.D.) | Major | Introduction to Artificial Neural Networks Technology, Neural Modelling, Input Coding Techniques, Adalene and Madalene, Multi-layer perception model using back propagation training, to Improve generalization BAM and the Hopfeld memory, Counter propagation network, self-organizing map. |
| ECE621M | Communication Systems | Basic | Topics covered in this course include modulation techniques, noise, transmitter and receiver circuits. |
| ECE621D | Communication Systems (for Ph.D.) | Basic | This course is intended for Ph.D. students. It includes topics such as modulation techniques, noise, and transmitter and receiver circuits. |
| ECE622M | Broadcast Engineering | Basic | This course helps graduate students understand the theoretical and practical aspects of AM, FM and Television broadcasting. The course covers the basics of broadcast engineering and progresses to the latest technologies related to broadcast engineering. Specifically, it covers broadcast antennas, broadcast studios, design of broadcast transmitters, automated programming, digital broadcasting and other advances in broadcast engineering. |
| ECE622D | Broadcast Engineering (for Ph.D.) | Basic | This course helps graduate students understand the theoretical and practical aspects of AM, FM and Television broadcasting. The course covers the basics of broadcast engineering and progresses to the latest technologies related to broadcast engineering. Specifically, it covers broadcast antennas, broadcast studios, design of broadcast transmitters, automated programming, digital broadcasting and other advances in broadcast engineering. |
| ECE623M | Vehicular Communications | Major | This course introduces emerging technologies, standards, and applications in vehicular communication systems. Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication design and challenges are studied and analyzed. Vehicular mobility modeling and technologies will also be introduced in this course. Emerging applications of vehicular communications pertaining to Intelligent Transportation Systems are also discussed. |
| ECE623D |
Vehicular Communications (for PhD)
|
Major | This is an extension of ECE623M intended for Ph.D. This course introduces emerging technologies, standards, and applications in vehicular communication systems. Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication design and challenges are studied and analyzed. Vehicular mobility modeling and technologies will also be introduced in this course. Emerging applications of vehicular communications pertaining to Intelligent Transportation Systems are also discussed. |
| ECE625M | Electromagnetic Compatibility | Major | This course begins with a brief overview of electromagnetic compatibility. Discussions will proceed with a review of electromagnetic principles, particularly those related to electromagnetic fields, radio frequency spectrum, interference, coupling, conduction, radiated emission, susceptibility, and immunity, including electromagnetic behaviour of electrical systems, devices, circuits, components, and materials. Health and safety issues will be dealt with together with the applicable regulations and standards. EMC tests and measurements, ppmethods of reducing the adverse effects of electromagnetic interference such as cabling, grounding, and shielding. will form part of the application of EMC principles in the design of electromagnetically compatible systems. |
| ECE625D | Electromagnetic Compatibility (for Ph.D.) | Major | This is an extension of ECE625M intended for Ph.D. students This course begins with a brief overview of electromagnetic compatibility. Discussions will proceed with a review of electromagnetic principles, particularly those related to electromagnetic fields, radio frequency spectrum, interference, coupling, conduction, radiated emission, susceptibility, and immunity, including electromagnetic behaviour of electrical systems, devices, circuits, components, and materials. Health and safety issues will be dealt with together with the applicable regulations and standards. EMC tests and measurements, ppmethods of reducing the adverse effects of electromagnetic interference such as cabling, grounding, and shielding. will form part of the application of EMC principles in the design of electromagnetically compatible systems. |
| ECE626M | Deep Learning Applications on Mobile Platform | Major | This course begins with a brief review of practical machine learning methodology and the fast-growing field of deep learning. Discussions will proceed with an overview of deep learning applications on the mobile platform, including Convolutional Neural Networks (CNN) for mobile,Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gate Recurrent Unit (GRU), Convolutional-GRU architecture, and Reinforcement Learning (RL) for mobile devices. Class examples and demos will be implemented using the open-source Tensorflow (TF) machine learning library and sample mobile applications will be developed in Android platform. |
| ECE626D | Deep Learning Applications on Mobile Platform (for PhD) | Major | This course begins with a brief review of practical machine learning methodology and the fast- growing field of deep learning. Discussions will proceed with an overview of deep learning applications on the mobile platform, including Convolutional Neural Networks (CNN) for mobile,Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gate Recurrent Unit (GRU), Convolutional-GRU architecture, and Reinforcement Learning (RL) for mobile devices. Class examples and demos will be implemented using the open-source Tensorflow (TF) machine learning library and sample mobile applications will be developed in Android platform. |
| ECE630M | Computational Photography | Major | The typical image acquisition pipeline begins with light entering some optical system and ultimately ends up being read by an optical sensor. However, the usual approaches result to a lot of information being discarded in the process. Computational photography is a field of study that pushes for the capture or extraction of information beyond what the typical camera can capture, effectively producing photographs which cannot be taken using a normal camera. This course tackles some of the problems under computational photography along with potential solutions to the said problems. In particular, we look at the image acquisition process, image fusion techniques, resizing and enhancement, as well as HDR imaging. A brief introduction to plenoptic imaging-a means of capturing 4D light fields instead of 2D images-is given. Throughout the entire course, hands-on exercises using MATLAB will be used to supplement the discussions. |
| ECE631M | Digital Signal Processing | Major | This course deals with the introduction to discrete-time signals and systems, discrete convolution and correlation, Z-transform, sampling and reconstruction, quantization, Discrete-time Fourier Transform, Discrete Fourier Tranform, Fast Fourier Transform, Design of IFR and ITR filters, Digital Filter Structure, and Effects of finite register length. |
| ECE631D | Digital Signal Processing (for Ph.D.) | Major | This is an extension of ECE6310 intended for Ph.D. students. This course deals with the introduction to discrete-time signals and systems, discrete convolution and correlation, Z-transform, sampling and reconstruction, quantization, Discrete-time Fourier Transform, Discrete Fourier Transform, Fast Fourier Transform, Desifn of IFR and ITR filters, Digital Filter Structure, and Effects of finite register length. |
| ECE632M | Digital Signal Processing and Application | Major | This course deals with signal modelling, optimum filters, spectrum estimation, adaptive filters, and multirate signal processing. |
| ECE634M | Digital Signal Processor | Major | Covers the Programming of TMS320C XX Family of DSP¿s |
| ECE635M | DSP Application in Communication | Major | This course covers topics on Telephone line modems, speech digitization and compression, voice mail, and speech synthesis. |
| ECE635D | DSP Application in Communication (for Ph.D) | Major | This is an extension of ECE635M intended for PhD students. It deals with telephone line modems, speech digitization and compression, voice mail, speech synthesis, etc. |
| ECE637M | Advanced DSP and Filter Design | Major | This course deals with advanced analysis, design, and realization of digital filters; Fourier Transform algorithm implementations, finite wordlength arithmetic, fixed point implementation, limit cycles, noise shaping, decimation and interpolation, multi-rate filter design, Hilbert transformers, analytic signal generation, and basic adaptive filtering. |
| ECE638M | Image Processing Fundamentals | Major | Despite the abundance of images in the modern world, many of the problems with images persist to this very day. As digital images grow in resolution, the amount of memory they consume likewise increase making the task of image compression equally as relevant today. To further complicate the problem, images are often corrupted with varying levels of noise. The presence of noise reduces the compressibility of data while reducing the quality of images in general which makes the problem of image denoising important as well. To tackle these problems, we look into the underlying properties of images and the ways of representing images. This course introduces the different properties and representations while going through common and state-of-the-art techniques associated with different image processing problems. Exercises using MATLAB will be provided throughout the entire course to supplement the different discussions. |
| ECE638D | Image Processing Fundamentals (for PhD) | Major | Despite the abundance of images in the modern world, many of the problems with images persist to this very day. As digital images grow in resolution, the amount of memory they consume likewise increase making the task of image compression equally as relevant today. To further complicate the problem, images are often corrupted with varying levels of noise. The presence of noise reduces the compressibility of data while reducing the quality of images in general which makes the problem of image denoising important as well. To tackle these problems, we look into the underlying properties of images and the ways of representing images. This course introduces the different properties and representations while going through common and state-of-the-art techniques associated with different image processing problems. Exercises using MATLAB will be provided throughout the entire course to supplement the different discussions. |
| ECE639M | Compressive Sensing and Sparse Representations | Major | The technique known as compressive sensing is a recent development in the field of signal processing that the reconstruction of a complete signal from incomplete measurements. In essence, compressive sensing allows one to find the inverse of underdetermined systems by placing a sparsity constraint on the variables. This course tackles the foundations of compressive sensing and the underlying sparse representations of signals. The different algorithms used to find dictionaries and solutions with the compressive sensing framework shall also be discussed in this course. To supplement the lectures, hands-on exercises using MATLAB will be used throughout the duration of the course. |
| ECE640M | Discrete Control System | Major | This course introduces graduate students to the theory and practice of Control System Engineering, emphasizing on Discrete Time Control Systems to Modern Control theory. Various control systems will be discussed ¿ emphasizing how the different system variables interact and how they affect overall system performance. Numerical simulations will be performed to further understand Control System theories using Matlab and Simulink. |
| ECE640D | Discrete Control System (for Ph.D) | Major | This course is an extension of ECE640M intended for PhD students. It introduces graduate students to the theory and practice of Control System Engineering, emphasizing on Discrete Time Control Systems to Modern Control theory. Various control systems will be discussed ¿ emphasizing how the different system variables interact and how they affect overall system performance. Numerical simulations will be performed to further understand Control System theories using Matlab and Simulink. |
| ECE650M | Switching Theory | Major | This course covers topics on Number system and codes, Boolean algebra, combinational circuit minimization sequential circuit analysis and synthesis, and sequential circuit state minimization. |
| ECE650D | Switching Theory (for Ph.D.) | Major | This is an extension of ECE650M intended for PhD students. It deals with number system and codes, Boolean algebra, combinational circuit minimization sequential circuit analysis and synthesis, sequential circuit state minimization. |
| ECE651M | Advanced Computer Organization | Major | This course deals with multi-processing and multi-programming; High level computer language array and different computer networks. |
| ECE651D | Advanced Computer Organization (for Ph.D) | Major | This course is an extension of ECE651M intended for PhD students. It deals with multi-processing and multi-programming; high level computer language array and different computer networks. |
| ECE652M | Integrated Circuit Electronics | Major | This course deals with the study of design and applications of existing commercial and custom made linear and digital IC¿s; concepts of VLSI design, etc. |
| ECE652D | Integrated Circuit Electronics (for Ph.D) | Major | This course is an extension of ECE652M intended for PhD students. It deals with the study of design and applications of existing commercial and custom made linear and digital IC¿s; concepts of VLSI design, etc |
| ECE653M | Microprocessing and Interfacing Techniques | Major | This course covers the introduction to the M68HC11, M68HC11 Reset and Interrupts, Parallel I/O, Serial Communication Interface (SCI) and Serial Peripheral Interface (SPI), Free-running counter and Input Captures, Real-time Interrupts and Pulse accumulator, Analog-to-Digital Conversions and Fuzzy Inference, Expanded Multiplexed Mode. |
| ECE653D | Microprocessing and Interfacing Techniques (for Ph.D.) | Major | This course covers the introduction to the M68HC11, M68HC11 Reset and Interrupts, Parallel I/O, Serial Communication Interface (SCI) and Serial Peripheral Interface (SPI), Free-running counter and Input Captures, Real-time Interrupts and Pulse accumulator, Analog-to-Digital Conversions and Fuzzy Inference, Expanded Multiplexed Mode. |
| ECE654M | Semi-Conductor Technology and Design | Major | This course discusses topics on Thin film technology; preparation of wafers, circuits. Photolithographic process, wafer fab, IC design, and VLSI design. |
| ECE654D | Semi-Conductor Technology (for Ph.D.) | Major | Thin film technology: preparation of wafers, circuits. Photolithographic process, wafer fab, IC design , VLSI design. |
| ECE655M | Digital Circuit Fundamentals With Vhdl Programming | Major | This course covers the fundamentals of switching theory, logic concepts, logic circuit components, combinatorial logic circuit design and optimization, and sequential circuit design. Students will also be trained to design digital circuits using Hardware Description Language (HDL). |
| ECE656M | Embedded Systems Design And Prototyping 1 | Major | The course deals with the low-level RTL implementation of embedded system IP cores which include arithmetic circuits, memory controllers, Input and Output controllers such as the VGA controller, PS2 mouse and keyboard controllers, and UART using the FPGA (Field Programmable Gate Array) Design Flow, and the integration of these components to address given computational requirement. Implementation is carried out on FPGA Development Boards to demonstrate functionality of the system. |
| ECE658D | Special Topics in Energy & Environment (Geothermal) | Major | This course begins with a review of the energy sector in the Philippines with special attention to geothermal energy. The course will cover conventional and innovative power cycles for geothermal power generation to enable the student to model and compare the performances of the cycle. The course will focus on conventional power generation technology, i.e. , Rankine cycle and Organic Rankine cycle, and compare it with relatively new technologies, e.g. Kalina Power cycle. The course will also cover the study and comparison of various working fluids such as steam, ammonia-water mixtures and organic fluids used in geothermal power generation. Power plant economics and environmental impacts will also be covered. |
| ECE6590 | Analog Circuit Design | Major | Analysis and design of amplifiers and power supplies. |
| ECE659D | Analog Circuit Design (for Ph.D.) | Major | Analysis and design of amplifiers and power supplies. |
| ECE660M | Electronic Amplifiers | Major | Covers Linear and no-linear models of active devices at low and high frequencies; Theory and design of wideband low-pass amplifiers; distributed amplifiers and large-signal amplifiers. |
| ECE660D | Electronic Amplifiers (for Ph.D.) | Major | This course is an extension of ECE660M intended for Ph.D. students. It covers topics on Linear and non-linear models of active devices at low and high frequencies, theory and design of wideband low-pass amplifiers, distributed amplifiers and large-signal amplifiers |
| ECE661M | Fuzzy Logic | Major | This course discusses the foundation and concepts of fuzzy logic systems; Fuzzy logic controllers (FLC’s) Design and Analysis issues; Fuzzy logic system implementation and applications. |
| ECE661D | Fuzzy Logic (for Ph.D.) | Major | This is an extension of ECE 6610 for intended for PhD students. This graduate course deals with the discussion of foundation of fuzzy, fuzzy logic controllers (FLC’s) Design and analysis issues, fuzzy logic software-hardware design and implementation and application. |
| ECE662M | Linear Systems Theory | Major | This course discusses the theories regarding linear systems. The students will the thought of the challenges of characterizing complex systems from Simple linear systems to Shift-invariant systems. |
| ECE662D | Linear Systems Theory (for Ph.D) | Major | This course is an extension of ECE662M intended for PhD students. This subject discusses the theories regarding linear systems. The students will the thought of the challenges of characterizing complex systems from Simple linear systems to Shift-invariant systems. |
| ECE663M | Introduction To Robotics I | Major | This course is aimed to provide the first part of the introductory robotics knowledge for graduate students in Engineering. The lecture includes the basics in spatial descriptions and transformations, manipulator forward and inverse kinematics. This course is composed of lecture and computer laboratory using Open Dynamics Engine. The student is expected to have a working knowledge in C/C++ and a background in Elementary Linear Algebra. |
| ECE663D | Introduction To Robotics I ( For PhD ) | Major | This subject is an extension of ECE663M intended for PhD students. This course is aimed to provide the first part of the introductory robotics knowledge for graduate students in Engineering. The lecture includes the basics in spatial descriptions and transformations, manipulator forward and inverse kinematics. This course is composed of lecture and computer laboratory using Open Dynamics Engine. The student is expected to have a working knowledge in C/C++ and a background in Elementary Linear Algebra. |
| ECE664M | Introduction To Robotics II | Major | This course is aimed to provide second part of the introductory robotics knowledge for graduate students in Engineering. The lecture includes manipulator dynamics, forces and torque interactions with environments, and trajectory planning. This course is composed of lecture and computer laboratory using Open Dynamics Engine. The student is expected to have a working knowledge in C/C++ and a background in Elementary Linear Algebra. |
| ECE664D | Introduction To Robotics II ( For Phd ) | Major | This course is an extension of ECE664M intended for PhD students. This subject is aimed to provide second part of the introductory robotics knowledge for graduate students in Engineering. The lecture includes manipulator dynamics, forces and torque interactions with environments, and trajectory planning. This course is composed of lecture and computer laboratory using Open Dynamics Engine. The student is expected to have a working knowledge in C/C++ and a background in Elementary Linear Algebra. |
| ECE665M | Robotics And Mechatronics | Major | Covers topics on Robotics applications to Industries, Software and hardware design of industrial robots, Manufacturing and process automation, Computer Integrated Manufacturing Systems, Programmable logic controllers concepts and applications. |
| ECE665D | Robotics And Mechatronics (For Ph.D) | Major | This course is an extension of ECE665M intended for Ph.D. students. It covers topics such as Robotics applications to Industries, Software and hardware design of industrial robots, Manufacturing and process automation, Computer Integrated Manufacturing Systems, Programmable logic controllers concepts and applications. |
| ECE666M | Power Electronics | Major | This course provides ECE graduate students an understanding of the application of power semiconductor components and devices to power system problems; power control, conditioning, processing and switching. This course is supplemented by circuit and mathematical simulations using Matlab and design projects. |
| ECE666D | Power Electronics (for Ph.D) | Major | This course is an extension of ECE666M intended for PhD students. This subject provides ECE graduate students an understanding of the application of power semiconductor components and devices to power system problems; power control, conditioning, processing and switching. This course is supplemented by circuit and mathematical simulations using Matlab and design projects. |
| ECE667M | Advanced Robotics with Laboratory | Major | This graduate course aims to educate students about the concepts behind robotics technology that are in research, industries, and manufacturing processes. Studies on the robot kinematics and transformations are conducted. Mathematics of robot manipulation and manipulator modeling are discussed. Robotics sensory devices are investigated to demonstrate clearly the role played by internal sensors in the control of individual robotic joint, and also by external sensors in providing the robot with knowledge about its external environment. Special attention is focused on the development of multi-robot cooperative system. Theoretical concepts and real time applications of cooperative mobile robots are studied. Computer considerations for vision, path planning and navigation for autonomous mobile robots are analyzed. The students are required to do research activities on topics concern |
| ECE667D | Advanced Robotics with Laboratory (for Ph.D.) | Major | This is an extension of ECE 6670 intended for for PhD students. This graduate course aims to educate students about the concepts behind robotics technology that are in research, industries, and manufacturing processes. Studies on the robot kinematics and transformations are conducted. Mathematics of robot manipulation and manipulator modeling are discussed. Robotics sensory devices are investigated to demonstrate clearly the role played by internal sensors in the control of individual robotic joint, and also by external sensors in providing the robot with knowledge about its external environment. Special attention is focused on the development of multi-robot cooperative system. Theoretical concepts and real time applications of cooperative mobile robots are studied. Computer considerations for vision, path planning and navigation for autonomous mobile robots are analyzed. The students are required to do research activities on topics concerning robotic control systems. |
| ECE668M | Computational Intelligence / Soft Computing | Major | Computational Intelligence reflects the essential role of building Intelligent Systems. It comprises the fairly recent areas of evoluationary computing, fuzzy computing, neuro-computing, as well as some related machine learning processes. The course presents both theory and applications to motivate the understanding by providing real-worl useful applications of Artificial Intelligence techniques. The course offers topics on Fuzzy Logic and Fuzzy Control, Connectionist Modeling and Neural Networks. |
| ECE668D | Computational Intelligence / Soft Computing (for Ph.D.) | Major | This course is an extension of ECE668M intended for PhD students. Computational intelligence reflects the essential role of building Intelligent Systems. It comprises the fairly recent areas of evolutionary computing, fuzzy computing, neuro-computing, as well as some related machine learning processes. The course presents both theory and applications to motivate the understanding by providing real-world useful applications of Artificial Intelligence techniques. The course offers topics on Fuzzy Logic and Fuzzy Control, Connectionist Modeling and Neural Networks. |
| ECE669M | Robot Motion Planning | Major | This course is aimed to provide the first part of the introductory robotics knowledge for graduate students in Engineering. The lecture includes the basics in spatial descriptions and transformations, manipulator forward and inverse kinematics. This course is composed of lecture and computer laboratory using Open Dynamics Engine. The student is expected to have a working knowledge in C/C++ and a background in Elementary Linear Algebra. |
| ECE669D | Robot Motion Planning (for Ph.D) | Major | This course is aimed to provide the first part of the introductory robotics knowledge for graduate students in Engineering. The lecture includes the basics in spatial descriptions and transformations, manipulator forward and inverse kinematics. This course is composed of lecture and computer laboratory using Open Dynamics Engine. The student is expected to have a working knowledge in C/C++ and a background in Elementary Linear Algebra. |
| ECE670M | Synthesis of Non-Linear Network | Major | This course focuses on the Synthesis of Non-Linear Networks. Topics covered range from theoretical and computational aspects, to practical applications. The teaching approach will be both qualitative and quantitative. |
| ECE670D | Synthesis of Non-Linear Network (for Ph.D.) | Major | This course is an extension of ECE670M intended for PhD students. It focuses on the Synthesis of Non-Linear Networks. Topics covered range from theoretical and computational aspects, to practical applications. The teaching approach will be both qualitative and quantitative. |
| ECE671M | Advanced Feedback Control Systems | Major | This course deals with the analysis and design of systems employing electronic feedback controls and transducers. |
| ECE671D | Advanced Feedback Control System (for Ph.D.) | Major | Analysis and design of systems employing electronic feedback controls; transducers. |
| ECE672M | Analog Circuit Fundamentals | Major | This course covers the following topics: MOS transistor models, MOS single-transistor amplifier, differential pair, current mirrors, output transcoductance amplifier, active and switched capacitor filters, noise considerations, frequency cosiderations, and temperature stability. |
| ECE673M | Semiconductor Devices Physics | Major | This course deals with the physics of semiconductor devices. Physical aspects of semiconductors will be presented, followed by: diodes, bipolar junction transistors, and MOSFETs. Topics to be covered in the course include: Basic quantum mechanics necessary to describe how electrons behave in atoms, free space, and solid; Band theory of solid: concept of conduction/valence band; Concepts of electrons, holes, doping, carrier concentration, scattering, and mobility; Behavior of electrons inside semiconductor when a field or concentration gradient has been present ; Basic operation of p-n junction (diode); Operation of light emitters and detectors; Operation of bipolar junction devices; Operation of Metal Oxide Semiconductor Field Effect Transistor (MOSFET) |
| ECE674M | Microprocessor Core Architecture Design | Major | This is a laboratory intensive course that teaches the student how to design a pipelined microprocessor core using VHDL as entry tool. The students will first be oriented to the different parts of a microprocessor core namely: the program counter, the instruction memory, instruction register, the register bank, the arithmetic logic unit, the flag register, and the data memory. This will be followed by concept of pipelining, the von Neumann architecture vs. the Harvard Architecture. The concept of stalling and forwarding will be used to deal with conflicting operands arising from consecutive instructions. By the end of the course, the student would have been able to design, simulate and implement the microprocessor core using a set of instructions as stimulus. |
| ECE675M | VLSI Devices | Major | This course starts with introduction to semiconductor and its atomic structure. It also discusses semiconductor’s bonding model, energy band model, carrier properties and carrier action This is followed by Basics of microchip fabrication, PN Junctions, Diodes and MOSFET devices characteristics. This course also covers the submicron MOS and the short channel effects. |
| ECE675D | VLSI Devices (for Ph.D.) | Major | This subject is an extension of ECE675M intended for PhD students. This course starts with introduction to semiconductor and its atomic structure. It also discusses semiconductor’s bonding model, energy band model, carrier properties and carrier action This is followed by Basics of microchip fabrication, PN Junctions, Diodes and MOSFET devices characteristics. This course also covers the submicron MOS and the short channel effects. |
| ECE676M | Introduction to Application Specific Integrated Circuit Design | Major | This course introduces the students to the concept of semi-custom digital IC design. The course starts with learning digital circuit design using Hardware Description Language (HDL). The design approach covers behavioral modeling, structural modeling and Register Transfer Level modeling of digital systems. This is then followed by design issues related to synthesis, simulation mismatch and issues related to circuit implementation using standard cells library or Field Programmable Gate Arrays. |
| ECE676D | Introduction to Application Specific Integrated Circuit Design (for Ph.D.) | Major | This course is an extension of ECE676M intended for PhD students. It introduces the students to the concept of semi-custom digital IC design. The course starts with learning digital circuit design using Hardware Description Language (HDL). The design approach covers behavioral modeling, structural modeling and Register Transfer Level modeling of digital systems. This is then followed by design issues related to synthesis, simulation mismatch and issues related to circuit implementation using standard cells library or Field Programmable Gate Arrays. |
| ECE677M | Mixed Signal Electronics | Major | This course covers integrated circuits (IC), operational amplifiers and its applications, data converters, and mixed-signal systems. |
| ECE678M | Artificial Intelligence in ECE Simulations and Modeling | Major | This course aims to educate students about developing intelligent machines through computer simulations and modelling. Studies on actual derivation of equations describing the dynamics of the systems are discussed in order to model the real physical system. Techniques on making expert systems that model the expertise of a human expert are covered in this course. Studies on Computer Graphics and Data Structures are emphasized. The students are taught the concepts of data structures to be applied for game programming and computer animations. |
| ECE678D | Artificial Intelligence in ECE Simulations and Modeling (for Ph.D.) | Major | This course is an extension of ECE678M intended for Ph.D. students. This subject aims to educate students about developing intelligent machines through computer simulations and modelling. Studies on actual derivation of equations describing the dynamics of the systems are discussed in order to model the real physical system. Techniques on making expert systems that model the expertise of a human expert are covered in this course. Studies on Computer Graphics and Data Structures are emphasized. The students are taught the concepts of data structures to be applied for game programming and computer animations. |
| ECE680M | Synchronization of Chaos | Major | This course deals with the Chaos theory and concepts and modeling chaotic behavior of a dynamical system. |
| ECE680D | Synchronization of Chaos (for Ph.D.) | Major | This course is an extension of ECE680M intended for Ph.D. students. It discusses topics such as Chaos theory and concepts and Modeling chaotic behavior of a dynamical system. |
| ECE690M | Cybernetic Engineering | Major | This course introduces the students to the science of cybernetics and its possible applications in designing systems. Topics covered: history and principles of cybernetics, systems design concepts, modeling system components and interactions, applications of cybernetics. |
| ECE690D | Cybernetic Engineering (for Ph.D.) | Major | This is an extension of ECE6900 intended for Ph.D. students. This course gives an introduction to cybernetic engineering. It covers technical and philosophical aspects of biological cybernetics to the design of intelligent system and the control of complex systems. |
| ECE710M | Analog Integrated Circuit Design | Major | This course discusses the following topics: components integrated in MOS, basic lay outing rules, differential amplifier, current sources techniques, operational amplifiers, analog-to-digital and digital-to-analog converters. |
| ECE710D | Analog Integrated Circuit Design (for Ph.D.) | Major | This course is an extension of ECE710M intended for Ph.D. students. It includes topics such as components integrated in MOS, basic lay outing rules, differential amplifier, current sources techniques, operational amplifiers, analog-to-digital and digital-to-analog converters. |
| ECE711M | Digital Control Systems | Major | This course introduces the students to the principles of digital control systems and digital filter design. This includes the study and use of microprocessors/microcontrollers for control systems and the study of the mathematics and engineering of digital control systems. |
| ECE711D | Digital Control Systems (for PhD) | Major | This is an extension of ECE711M. This course introduces the students to the principles of digital control systems and digital filter design. This includes the study and use of microprocessors/microcontrollers for control systems and the study of the mathematics and engineering of digital control systems. |
| ECE712M | Metaheuristics in Computational Intelligence | Major | This course introduces the students to the principles of metaheuristics in computational intelligence such as ant colony optimization, particle swarm optimization, simulated annealing, and genetic algorithms. |
| ECE712D | Metaheuristics in Computational Intelligence (for PhD) | Major | This graduate course is an extension of ECE712M intended for Ph.D. students. It introduces the students to the principles of metaheuristics in computational intelligence such as ant colony optimization, particle swarm optimization, simulated annealing, and genetic algorithms. |
| ECE713M | Modern Control Systems Engineering | Major | This course introduces the students to the principles of modern control systems theory and engineering. This includes the study and use of microprocessors/microcontrollers for control systems and the study of the mathematics of modern control theory. |
| ECE713D | Modern Control Systems Engineering (for PhD) | Major | This is an extension of ECE713M intended for Ph.D. students. This course introduces the students to the principles of modern control systems theory and engineering. This includes the study and use of microprocessors/microcontrollers for control systems and the study of the mathematics of modern control theory. |
| ECE714M | Inductive Rule- Based Systems | Major | This course focuses on inductive rule based methods based on rough set theory. Topics covered range from theoretical and computational aspects, to practical applications. Students are expected to do a synopsis of a published article as a midterm project, and an original term paper demonstrating an application of significant research interest. |
| ECE714D | Inductive Rule- Based Systems (for Ph.D) | Major | This course is an extension of ECE714M intended for PhD students. It focuses on inductive rule based methods based on rough set theory. Topics covered range from theoretical and computational aspects, to practical applications. Students are expected to do a synopsis of a published article as a midterm project, and an original term paper demonstrating an application of significant research interest. |
| ECE715M | Machine Vision and Image Processing | Major | The course focuses on image processing theory as well as the application of imaging in the design and implementation of systems for machine vision in the real world. Topics include perception of 3D scene structure from stereo, motion, and shading; image filtering, smoothing, edge detection; segmentation and grouping; texture analysis; learning, recognition, and search; tracking and motion estimation. |
| ECE715D | Machine Vision and Image Processing (for Ph.D.) | Major | This course is an extension of ECE715M intended for PhD students. It focuses on image processing theory as well as the application of imaging in the design and implementation of systems for machine vision in the real world. Topics include perception of 3D scene structure from stereo, motion, and shading; image filtering, smoothing, edge detection; segmentation and grouping; texture analysis; learning, recognition, and search; tracking and motion estimation. |
| ECE720M | Genetic Algorithm | Major | This course aims to educate students about the concepts and uses of genetic algorithm in search, optimization, and machine learning. It covers the fundamental theory involved and gives detailed design examples involving both software and system optimization. Genetic Algorithm has emerged as a viable approach in control engineering and IT application. It is not only useful for very complex, ill defined and non-linear systems which cannot be solved by conventional algorithms, but is also useful in improving the performance of systems which can be solved by conventional techniques but with poor quality.Genetic algorithms are algorithms for optimization and learning based on the mechanism of genetic evolution. It gives solutions to problems using a probabilistic optimization method based on evolution strategies as nature solves the problem of adapting living organisms to the harsh realities of life in a hostile world. |
| ECE720D | Genetic Algorithm (for PhD) | Major | This course is an extension of ECE720M intended for PhD students. This course aims to educate students about the concepts and uses of genetic algorithm in search, optimization, and machine learning. It covers the fundamental theory involved and gives detailed design examples involving both software and system optimization. Genetic Algorithm has emerged as a viable approach in control engineering and IT application. It is not only useful for very complex, ill defined and non-linear systems which cannot be solved by conventional algorithms, but is also useful in improving the performance of systems which can be solved by conventional techniques but with poor quality. Genetic algorithms are algorithms for optimization and learning based on the mechanism of genetic evolution. It gives solutions to problems using a probabilistic optimization method based on evolution strategies as nature solves the problem of adapting living organisms to |
| ECE721M | Computer Graphics for Engineers | Major | This course will discuss the techniques of computing and rendering 3-dimensional objects in the computer screen. The student will become more proficient in C programming language. The Open Graphics Library (OpenGL) will be used as the implementation platform. This course has a computer laboratory sessions using Microsoft Visual Studio. The student is expected to have a working knowledge in C. |
| ECE721D | Computer Graphics for Engineers (for Ph.D) | Major | This course will discuss the techniques of computing and rendering 3-dimensional objects in the computer screen. The student will become more proficient in C programming language. The Open Graphics Library (OpenGL) will be used as the implementation platform. This course has a computer laboratory sessions using Microsoft Visual Studio. The student is expected to have a working knowledge in C. |
| ECE722M | Computational Optimization for Engineers | Major | This course will discuss methods of finding optimal solutions to real-world problems at some given constraints. The topic will cover linear optimization and non-linear constrained optimization. At the end of the course, the student is expected to be able to perform linear and non-linear constrained optimization computations to find optimal solutions considering real-world situations. This course has a computer laboratory component using Matlab. |
| ECE722D | Computational Optimization for Engineers (for Ph.D.) | Major | This course will discuss methods of finding optimal solutions to real-world problems at some given constraints. The topic will cover linear optimization and non-linear constrained optimization. At the end of the course, the student is expected to be able to perform linear and non-linear constrained optimization computations to find optimal solutions considering real-world situations. This course has a computer laboratory component using Matlab. |
| ECE730M | Power Line Communications | Major | The course aims to familiarize the students with a type of communications technique that is useful in smart grid applications, home automation, and automatic meter reading. The topics cover PLC standards, channel characterization, PLC parameters measurements, modulation and coding techniques, noise and attenuation, and current researches involving the same. |
| ECE730D | Power Line Communications (for PhD) | Major | This course is an extension of ECE730M intended for Ph.D. The course aims to familiarize the students with a type of communications technique that is useful in smart grid applications, home automation, and automatic meter reading. The topics cover PLC standards, channel characterization, PLC parameters measurements, modulation and coding techniques, noise and attenuation, and current researches involving the same. |
| ECE811M | Special Topics in Communication | Major | This course introduces graduate students to the technologies and the latest trends in global electronic communication. The topics include: Analog and digital terrestrial broadcast systems, cable television, satellite communications, microwaves, pre-recorded media and shared networking technologies such as the internet. The concepts learned will be applied to solve real-world problems relating to the convergence of technologies and secured distribution of signals worldwide. |
| ECE811D | Special Topics in Communication (for Ph.D.) | Major | This is an extension of ECE8110 intended for Ph.D. students. This course introduces graduate students to the technologies and the latest trends in global electronic communication. The topics include: analog and digital terrestrial broadcast systems, cable television, satellite communications, microwaves, pre-recorded media and shared networking technologies such as the internet. The concepts learned will be applied to solve real-world problems relating to the convergence of technologies and secured distribution of signals worldwide. |
| ECE812M | Special Topics in Electronics | Major | This course is handled by local or foreign visiting professors or distinguished industry practitioners specializing in Electronics. The content of this course varies depending on the professor’s field of specialization. |
| ECE812D | Special Topics in Electronics (for PhD) | Major | This course is handled by local or foreign visiting professors or distinguished industry practitioners specializing in Electronics. The content of this course varies depending on the professor’s field of specialization. |
| ECE813M | Special Topics in DSP | Major | This course deals with Digital Speech/Image Processing such as coding, enhancement, recognition, filtering, Audio/Video coding for Videoconferencing, and DSP applied in Communications. |
| ECE813D | Special Topics in DSP (for Ph.D.) | Major | This course deals with Digital Speech/Image Processing such as coding, enhancement, recognition, filtering, Audio/Video coding for Videoconferencing, and DSP applied in Communications. |
| ECE814M | Fractional Order Control Systems | Major | This course advances the student to the application of fraction order calculus to control systems. |
| ECE814D | Fractional Order Control Systems (for PhD) | Major | This is an extension of ECE814M intended for PhD students. This course advances the students to the application of fraction order calculus to control systems. |
| ECE815M | Fractional Order Calculus for Signals and Systems | Major | This course advances the student to the theory of fractional order calculus and its applications to signals processing and system theory. |
| ECE815D | Fractional Order Calculus for Signals and Systems (for PhD) | Major | This is an extension of ECE815M intended for PhD students. This course advances the student to the theory of fractional order calculus and its applications to signals processing and system theory. |
| ECE820D | Seminar in Ph.D. ECE | Major | This course is intended for Ph.D. students in preparation for their Ph.D. dissertation. This includes attendance to seminars / conferences and paper presentations of topics related to their dissertation. |
| ECE8310 | Practicum 1 | Research | ECE Project 1 |
| ECE8320 | Practicum 2 | Research | ECE Project 2 |
| ECE8330 | Practicum 3 | Research | ECE Project 3 |
| ECE8410 | Directed Research 1 | Research | Supervised Research 1 |
| ECE8420 | Directed Research 2 | Research | Supervised Research 1 and Project Output Presentation |
| ECE843D | Directed Research 3 | Research | Supervised Research 3 |
| ECE851M | Thesis 1 | Research | ECE Research Methods 1 |
| ECE852M | Thesis 2 | Research | ECE Research Methods 2 |
| ECE853M | Thesis 3 | Research | ECE Research Methods 3 |
| ECE854M | Thesis 4 | Research | ECE Research Methods 4 |
| ECE855M | Thesis 5 | Research | ECE Research Methods 5 |
| ECE856M | Thesis 6 | Research | ECE Research Methods 6 |
| ECE857M | Thesis 7 | Research | ECE Research Methods 7 |
| ECE858M | Thesis 8 | Research | ECE Research Methods 8 |
| ECE859M | Thesis 9 | Research | ECE Research Methods 9 |
| ECE951D | Doctoral Dissertation 1 | Research | Doctoral Research Methods 1 |
| ECE952D | Doctoral Dissertation 2 | Research | Doctoral Research Methods 2 |
| ECE953D | Doctoral Dissertation 3 | Research | Doctoral Research Methods 3 |
| ECE954D | Doctoral Dissertation 4 | Research | Doctoral Research Methods 4 |
| ECE955D | Doctoral Dissertation 5 | Research | Doctoral Research Methods 5 |
| ECE956D | Doctoral Dissertation 6 | Research | Doctoral Research Methods 6 |
| ECE957D | Doctoral Dissertation 7 | Research | Doctoral Research Methods 7 |
| ECE958D | Doctoral Dissertation 8 | Research | Doctoral Research Methods 8 |
| ECE959D | Doctoral Dissertation 9 | Research | Doctoral Research Methods 9 |
| ECE960D | Doctoral Dissertation 10 | Research | Doctoral Research Methods 10 |
| ECE961D | Doctoral Dissertation 11 | Research | Doctoral Research Methods 11 |
| ECE962D | Doctoral Dissertation 12 | Research | Doctoral Research Methods 12 |
| ECE963D | Doctoral Dissertation 13 | Research | Doctoral Research Methods 13 |
| ECE964D | Doctoral Dissertation 14 | Research | Doctoral Research Methods 14 |
| ECE965D | Doctoral Dissertation 15 | Research | Doctoral Research Methods 15 |