Academics

Curriculum

Academics

Curriculum

Curriculum

Introduction to Optimization Techniques

Subject No.
Research
Credit
Classification
EE424
Computer, Communication, Signal
3
Elective

The primary objective of this course is to present fundamental concepts and basic techniques of optimization with possible applications, which are essential for researches in circuit design, communications, signal processing, and control engineering. Topics include linear vector spaces and linear operators, linear estimation and filtering, functional analysis, optimal control, linear programming, nonlinear programming, dynamic programming, genetic programming (evolutionary computation), and neural networks.

Recommend

This course is to provide EE students with understanding and ability for design and implementation of data structure for problems solving in the EE area using computer programming. It deals with information representation using data abstraction, object-oriented programming, Algorithm analysis. Basic data structures to be covered are Array and Linked list, Stack and Queue, Tree, Graph, Sorting, and Hashing. Applications of such basic structures in EE problems using C++ are also covered.

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Signal, Communication, Computer
EE210

In this course, we discuss such various topics in probability theory and introductory random processes as probability, random variables, expectations, characteristic functions, random vectors, random processes, correlation functions, and power spectrum. From time to time, homework problems will be assigned, usually not for mandatory submission.

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Copyright ⓒ 2015 KAIST Electrical Engineering. All rights reserved. Made by PRESSCAT

Copyright ⓒ 2015 KAIST Electrical Engineering. All rights reserved. Made by PRESSCAT

34141 대전광역시 유성구 대학로 291
한국과학기술원(KAIST)
Tel. 042-350-3411   Fax. 042-350-3410

Copyright ⓒ 2015 KAIST Electrical
Engineering. All rights reserved.

Made by PRESSCAT