Intelligent Systems
Objective: This course is designed to equip students
to design Intelligent systems in the area of
engineering systems.
Credit: 2
Lecture Hours: 15
---Contents-1.Introduction: (3Hours)
Artificial Intelligence, Problem Solver, Expert System,
Knowledge Acquisition.
2.Agent system: (3Hours)
Agent
model,
Agent
design,
Agent
communication,
Agent
application
3.Concept Learning: (3Hours)
Fundamentals of Concept Learning, Version space, Decision Tree
4.Neural Networks: (3Hours)
McCulloch&Pitts model, Perceptron, Error Back Propagation,
Hopfield Net
5.Genetic Algorithms & Artificial Life: (3Hours)
Evolutionary Computation, Design of GA, Application of GA,
A-Life Model
--------References:
E.Rich : Artificial Intelligence, McGrow-Hill,1983
S.J. Russell & P.Norvig: Artificial Intelligence- A modan Appoach-, Prentice Hall,1955
J.R.Quinlan, C4.5 Programs for Machine Learning, Morgan Kaufmann,1993
P.D.WASSERMAN, Neural Computing, Van orstrand Reinhold,1989
D.E.Goldberg, Genetic Algorithm in search, Optimization and Machine Learning. AddisonWesley,
1989
C.G.Langton: Artificial Life, Addison Wesley,1989
・System Architecture
Objective: The lecture includes the digital hardware
design methodology for large digital systems such as
microprocessors and digital signal processors.
Hardware description language such as VHDL might be
also covered in the lecture if the attendees are
interested in such real computer aided design tools.
Credit: 2
Lecture Hours: 15
---Contents-1. Digital Circuit Design Basics: (3Hours)
Basic digital circuit elements such as, combinational Logic,
sequential logics, Flip-Flops, and Gates.
2. VHDL: (6Hours)
Hardware description language, digital circuit synthesis,
Simulation.
3. Microprocessor Basics: (3Hours)
Simple RISC processor organization and design, assembler
programming, operation model.
4. Final Project: (3Hours)
Microprocessor design or signal processing digital circuit
design by VHDL.
Design target changes every year.
--------References:

Douglas J. Smith: HDL CHIP DESIGN, Doone Publications, 1996

Douglas L. Perry: VHDL 3rd ed., McGraw-Hill, 1998

David A. Patterson, John L. Hennessy: Computer organization & Design –The hardware /
software interface-, Morgan Kaufmann Publisher, 1994
Iterdisciplinary Intelligent Systems Engineering Course (Doctor Course):
Electronics and Information Engineering

Advanced Acoustic Signal Processing:
Acoustic theory of speech production,
Time-domain models for speech processing,
Waveform coding of speech signal,
LPC and parametric coding,
Homomorphic speech processing,
Man-machine communication,
Special study on acoustic echo and noise canceling.
Information Engineering Course (Master Course):
Computer Systems

Signal Processing Theory:
Studying of 2-D systems and mathematical characteristics of images,
Visual perception of human and stereo imaging,
2-D image transforms,
Image enhancement by histogram and filtering,
Image restoration,
Image compression,
Edge detection algorithms