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It focuses on inductive rule based methods based on rough set theory. ECEM Information Theory and Coding Techniques Major Measures of information, probability, statistics application in communication, codings and error correcting codes. D Major This course will discuss the techniques of computing and rendering 3-dimensional objects in the computer screen. This course will discuss the techniques of computing and rendering 3-dimensional objects in the computer screen. This course deals with the Chaos theory and concepts and modeling chaotic behavior of a dynamical system. Major This course will discuss methods of finding optimal solutions to real-world problems at some given constraints. Computer considerations for vision, path planning and navigation for autonomous mobile robots are analyzed.

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. This course introduces the different properties and representations while going through common and state-of-the-art techniques associated with different image processing problems. Review of linear algebra and linear differential equation, existence and uniqueness, autonomous systems, phase portraits, nonlinear system, linearization, stability, perturbation, chaos and bifurcation. This course begins with a review of the energy sector in the Philippines with special attention to geothermal energy. This course discusses the theories regarding linear systems. This course aims to educate students about developing intelligent machines through computer simulations and modelling. COE 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.

Computational Intelligence reflects the essential role of building Intelligent Systems. This course involves mathematical concepts needed in the study of electronics and comminications.

It covers the fundamental theory involved and gives detailed design examples involving both software and system optimization. This is an extension of ECE intended for Ph.

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The course introduces the principle aspects of fiber optic telecommunications. Theoretical concepts and real time applications of cooperative mobile robots are studied. Grdauation 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.

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To further complicate the problem, images are often corrupted with vireo levels of noise. This course advances the student to the application of fraction order calculus to control systems.

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Robotics sensory devices are investigated to speecb 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. This course introduces graduate students to the theory and practice of Control System Engineering, emphasizing on Discrete Time Control Systems to Modern Control theory.

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This course helps graduate students understand the theoretical and practical aspects of AM, FM and Television broadcasting. 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. ECEM 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.

The students are required to do research activities on topics concern.

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The course will focus on conventional power generation technology, i. This course begins with a brief overview of electromagnetic compatibility. ECEM Computational Optimization graduxtion Engineers Major This course will discuss methods of finding optimal solutions to real-world problems at some given constraints.

The course presents both theory and applications to motivate the understanding by providing real-worl useful applications of Artificial Intelligence techniques.

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Studies on Computer Graphics graduatuon Data Structures are emphasized. The introduction is completed by treating the following system related aspects: 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.

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This subject discusses the theories regarding linear systems.

This course has a computer laboratory component using Matlab. The course introduces the principal aspects of fiber optic telecommunications. This course aims to educate students about the concepts and uses of genetic algorithm in search, optimization, and machine learning. Basic quantum mechanics necessary to describe how electrons behave in atoms, free space, and solid; Band theory of solid: This gtaduation is intended for Ph.

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To perform laboratory exercises that demonstrates standard measurement practices used in the television industry. This course deals with the analysis and design of systems employing electronic feedback controls and transducers. graduuation

ECEM 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 wngineer, decimation and interpolation, multi-rate filter design, Hilbert transformers, analytic signal generation, and basic adaptive filtering.

ECEM 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.

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The students will first be oriented to the different parts of enyineer microprocessor core namely: It comprises the fairly recent areas of evolutionary computing, fuzzy computing, neuro-computing, as well as some related machine learning processes. 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.