ICE502: Random Process
2015 Fall
This course aim at providing theoretical framework for the processing of random
signals, control, and communication. It is critical for advanced study of adaptive
signal process, statistical communication theory, detection and estimation theory,
spread spectrum, acoustic communications, radar and sonar signal processing, etc.
The students majoring in stochastic signal process are encouraged to take this course.
The course is taken by the notes provided on the website.
Prerequisites:
 Random Variables
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Digital signal processing
MATLAB programming
Instructor: 曾凡碩, F2016a/F6029, 07-5252000-4186;4478,
E-mail: fs.tseng@mail.nsysu.edu.tw
TA:
賴
信
彥
(m033070027@student.nsysu.edu.tw);
李
明
( b983011019@student.nsysu.edu.tw )
Time/Place: 0910-1200, Tuesday / EC2002
Text book:
[1] Scott L. Miller and Donald G. Childers, Probability and Random Processes with
Application to Signal Processing and Commincations, Elsevier Academic Press 2004.
(新月代理).
[2] A. Papoulis and S. U. Pillai, Probability, Random Variables, and Stochastic
Processes, 4th ed., 2002 (歐亞代理)
Reference: Robert M. Gray and Lee D. Davisson, An Introduction to Statistical Signal
Processing, Lectures.
Grading: Homeworks 40%; Midterm 30%; Final 30%.
Course outline:
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Unit 1: Introduction
Unit 2: Probability theory and random variables
Unit 3: Multiple variables
Unit 4: Random process
Unit 5: Advanced topic of random process
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Unit 6: Application to statistical signal process
Lecture slices are available at
http://140.117.166.224/Course_RP.htm
Course Format and Requirement:
This course follows the slices provided by the instructor. Students are expected to do
the homework when each unit is finished. There will be a midterm and final exam
during this semester. Full attendee is very encouraged and it will also be counted
towards the final grade.