Doctor of Philosophy in Computer Engineering (PHD-CPE)

ECE610D

Data Communication Network Design

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.

ECE611D

Information Theory and Coding Techniques

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.

ECE612D

Radiowave Propogation and Antennas

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.

ECE613D

Applied Instrumentation in Broadcasting

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.

ECE614D

Microwave Techniques

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.

ECE615D

Optical Fiber Communications

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.

ECE617D

Wireless Communication

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 radio wave propagation, antennas and antenna systems, analysis and design of different wireless communications systems, e.g. satellite communication, microwave system, etc.

ECE618D

Advanced Electromagnetic Theory

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.

ECE619D

Network Achitecture

This course is an extension of ECE619M intended for PhD students. It deals with transmission protocols like TCP/IP, ATM, etc.

ECE621D

Communications Systems

This course is an extension of ECE619M intended for PhD students. It deals with transmission protocols like TCP/IP, ATM, etc.

ECE622D

Broadcast Engineering

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.

ECE623D

Vehicular Communications

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.

ECE625D

Electromagnetic Compatibility

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.

ECE635D

DSP Applications in Communications

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.

ECE730D

Power Line Communications

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.

ECE811D

Special Topics in Communications

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.

ECE525D

Digital IC Design

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.

ECE666D

Introduction to Power Electronics

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.

ECE677D

Mixed Signal Electronics IC Design

This course is an extension of ECE677M intended for PhD students. It covers advanced topics in integrated circuits (IC), operational amplifiers and their applications, data converters, and mixed-signal systems.

ECE812D

Special Topics in Electronics

This course focuses on specific issues and/or topics of interest in electronics engineering.  It aims to cover important, emerging, technological, state-of-the-art, or advanced topics in electronics engineering. Topics are selected from the areas of interest and/or research of the instructor, and may include aspects of electronics engineering not directly studied in other courses. Topics may vary from term to term.

ECE620D

Neural Network

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.

ECE626D

Deep Learning in Mobile Computing

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), Transformers, and Reinforcement Learning (RL) for mobile devices. Class examples and demos will be implemented using the open-source TensorFlow Lite machine learning library and sample mobile applications will be developed in Android platform.

ECE630D

Computational Photography

Photography is often thought of as the art of capturing images and scenes into a more permanent medium such as analogue film or digital files. A lot of different factors are taken into consideration when capturing a photograph. These include lighting, lens and camera selection, and scene composition. This course tackles, at a fundamental level, how these factors come together to form a photograph. In particular, we will be looking at the concepts of light rays, light field imaging, camera optics, colour science, and hyperspectral imaging. It looks at how images acquired by a camera can be further processed to adjust the composition or get past imaging limitations. Throughout the entire course, hands-on exercises using MATLAB will be used to supplement the discussions

ECE631D

Digital Signal Processing

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.

ECE634D

Digital Signal Processor

This course covers the real-time implementation of DSP concepts using digital signal processors. C/C++ programming will be used to program the DSP processors. Development tools will be learned to perform debugging and visualization by plotting the signal in time and frequency domains. The input and output with the codec will be discussed to connect the DSP processor to the outside world. DSP theories and concepts such as the FIR, IIR filters, adaptive filters, and FFT will be discussed, focusing on their implementation in digital signal processors.

ECE638D

Image Processing Fundamentals

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.

ECE639D

Compressive Sensing and Sparse Representation

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.

ECE661D

Fuzzy Logic Control Systems

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.

ECE667D

Advanced Robotics with Laboratory

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.

ECE668D

Computational Intelligence/Soft Computing

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.

ECE678D

Artificial Intelligence in ECE – Simulation and Modelling

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.

ECE712D

Metaheuristics in Computational Intelligence

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.

ECE715D

Machine Vision and Image Processing

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.

ECE720D

Genetic Algorithm

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

ECE723D

Supervised Machine Learning Algorithms

This course covers the different algorithms used in supervised learning under machine learning. Algorithms on both regression and classification using Matlab will be discussed.

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.

COE996D

Oral Comprehensive Exam

The Oral Comprehensive Exam is a rigorous evaluation intended to ensure that PhD candidates possess the necessary foundational knowledge and research skills to proceed with their dissertation.

COE559D

Philosophy of Technology

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.

ECE820D

Seminar in PhD ECE

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.