TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Doctorate Of Science
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Learn entropy, relative entropy and mutual information. 2) Learn data compression. Markov chains. 3) Learn entropy rates, Hidden Markov models. 4) Learn Huffman, Hamming, zero-error codes. 5) Learn feedback capacity, differential entropy, maximum entropy 6) Learn rate distortion theory, network information theory.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Information theory and its relationship with Statistics. Shannon information theory, memoryless sources and channels. Entropy and information. Data compression and coding for secure communications.
COURSE CONTENTS	WEEK TOPICS 1st Week Entropy, relative entropy and mutual information. Entropy rates, 2nd Week Hidden Markov models. Markov chains. 3rd Week Data compression. 4th Week Huffman codes. Arithmetic coding. 5th Week Channel capacity. Channel coding theorem. 6th Week Zero-error codes. 7th Week Hamming codes. 8th Week Midterm Exam 9th Week Feedback capacity. 10th Week Differential entropy. 11th Week Gaussian channel, bandlimited channels. 12th Week Maximum entropy and spectral estimation. 13th Week Rate distortion theory. 14th Week Network information theory.
RECOMENDED OR REQUIRED READING	T. M. Cover (1991), Elements of Information Theory, John Wiley; D.J.C. Mackay (2005), Information Theory, Interference and Learning Algorithms, Cambridge.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 35 Assignment 1 12 Quiz 2 13 Total(%) 47 Contribution of In-term Studies to Overall Grade(%) 47 Contribution of Final Examination to Overall Grade(%) 53 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 3 3 Preparation for Quiz 0 0 0 Individual or group work 14 8 112 Preparation for Final exam 1 40 40 Course hours 14 3 42 Preparation for Midterm exam 1 30 30 Laboratory (including preparation) 0 0 0 Final exam 1 3 3 Homework 2 35 70 Total Workload 300 Total Workload / 30 10 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No