Prerequisites: 
Singlevariable calculus, and a solid background in linear algebra. Some familiarity with modular arithmetic might help, but is not required. We will eventually understanding something about finite fields, their structure and matrices/linear algebra over them. For this reason, the course has a slightly higher mathematical level than Math 5248. 
Instructor:  Victor Reiner (You can call me "Vic"). 
Office: Vincent Hall 256 Telephone (with voice mail): (612) 6256682 Email: reiner@math.umn.edu 

Classes: 
Monday, Wednesday 3:355:00pm in Ford Hall 110 
Office hours:  Mon, Tues, Fri at 2:30pm, and by appointment. 
Course content: 
This is an introductory course in the mathematics of codes for communication designed to achieve compression of information and errordetecting/correction. We intend to cover much of the text by Garrett listed below, including treatment of
even though they are sometimes included in the title of the course. The topics covered are similar to when the course has been taught in the past by Prof. Paul Garrett, the author of our text A useful resource are his lecture transparencies and homeworks solutions from his crypto page. Here is my syllabus from last spring, when I first taught this class. This is not a course in

Text: 
The Mathematics of Coding Theory: Information, Compression, Error Correction and
Finite Fields
by Paul Garrett, Prentice Hall, 2004. A (nonrequired) supplemental text which has been used for part of this course in the past is Introduction to coding and information theory by Steven Roman, SpringerVerlag, 1997. There are a small number of topics we are likely to touch on that appear in Roman's book, but not in Garrett's: nonbinary Huffman coding, Plotkin bound, ReedMuller codes, Golay codes, latin squares. Here is Richard Ehrenborg's parlor trick using the Hamming binary [7,4,1]code that was demonstrated on the first day of class. 
Homework and exams:  There will likely be 6 homework assignments due generally every other week,
except for
Late homework will not be accepted. Early homework is fine, and can be left in my mailbox in the School of Math mailroom near Vincent Hall 105. Collaboration is encouraged as long as everyone collaborating understands thoroughly the solution, and you write up the solution in your own words, along with a note at the top of the homework indicating with whom you've collaborated. Homework solutions should be wellexplained the grader will be told not to give credit for an unsupported answer. 
Grading: 
Homework = 50% of grade Each of 2 midterms = 15% of grade Final exam 20% of grade. Complaints about the grading should be brought to me. 
Policy on incompletes:  Incompletes will be given only in exceptional circumstances, where the student has completed almost the entire course with a passing grade, but something unexpected happens to prevent completion of the course. Incompletes will never be made up by taking the course again later. You must talk to me before the final exam if you think an incomplete may be warranted. 
Other expectations  This is a 4credit course, so I would guess that the average student should spend about 8 hours per week outside of class to get a decent grade. Part of this time each week would be wellspent making a first pass through the material in the book that we anticipate to cover in class that week, so that you can bring your questions/confusions to class and ask about them. 
Assignment or Exam  Due date  Problems, mainly from Garrett's book  

Homework 1  Wed Jan. 31 
From Garrett's text: 1.28, 1.31, 1.33 2.03 (Note: I moved problem 2.04 to HW2) 3.02,3.05 Not from text: A. Consider these three collections C1, C2, C3 of codewords: C1={0,10,110,1110,1111} C2={0,10,110,1110,1101} C3={0,01,011,0111,1111} Indicate for each (with explanation) whether or not it is (a) uniquely decipherable, (b) instantaneous. B. Does there exist a binary code which is instantaneous and has code words with lengths (1,2,3,3)? If not, prove it. If so, construct one. (Note: I am removing this problem from the HW's: C. State and prove the precise conditions under which a random variable X on a finite probability space has entropy H(X) equal to zero.) 

Homework 2  Wed Feb. 14 
From Garrett's text: 2.04 4.01, 4.02, 4.04, 4.05, 4.06, 4.11 Not from text: Let p be a probability between 0 and 1. Explain why a noisy channel with input and output alphabets both {0,1} and the following probabilities is called a useless channel: P(0 received  0 sent)=p P(0 received  1 sent)=p P(1 received  0 sent)=1p P(1 received  1 sent)=1p 

Midterm exam 1  Wed. Feb. 21  Midterm exam 1 in PostScript, PDF.  
Homework 3  Wed Mar. 7 
From Garrett's text: 5.01, 02, 03, 04, 05, 08 6.01, 03, 07, 22, 49, 50, 52, 80 (Prob. 6.37 is moved to HW4) 

Homework 4  Wed Mar. 28 
From Garrett's text: 6.30, 31, 37, 57, 81 8.17 9.11, 12 10.04, 08, 11 11.11 12.06, 12.10, 12.12, 12.14, 12.15 

Midterm exam 2  Wed. Apr. 4  Midterm exam 2 in PostScript, PDF.  
Homework 5  Wed Apr. 18 
From Garrett's text: 12.01, 02, 04, 17, 19, 20 13.02, 05, 07, 09, 10 

Homework 6  Wed Apr. 25 (note 1week due date!) 
From Garrett's text: 14.02, 05 11.04, 05 15.03, 13  
Final exam  Wed. May 2  Final exam in PostScript, PDF. 