| Line 27: | Line 27: | ||
*[[ECE662_topic1_discussions|Week 1: Introduction and Expectations]] | *[[ECE662_topic1_discussions|Week 1: Introduction and Expectations]] | ||
*[[ECE662_topic2_discussions|Week 3: Is Bayes truly the best?]] | *[[ECE662_topic2_discussions|Week 3: Is Bayes truly the best?]] | ||
| + | *[[ECE662_topic3_discussions|Hw1: Discuss the first hw here.]] | ||
==Homework== | ==Homework== | ||
* [[hw0_ECE662Spring2010|HW0 - getting ready]] | * [[hw0_ECE662Spring2010|HW0 - getting ready]] | ||
| + | *[[hw1_ECE662Spring2010|HW1- Bayes rule for normally distributed features]] | ||
==References== | ==References== | ||
Revision as of 10:01, 9 February 2010
Contents
ECE662: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010
General Course Information
- Instructor: Prof. Boutin a.k.a. Prof. Mimi
- Office: MSEE342
- Email: mboutin at purdue dot you know where
- Class meets Tu,Th 12-13:15 in EE115
- Office hours are listed here
- Syllabus
- Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25
- Make up classes: to be announced. Please list the times when you cannot meet here
Discussions and Students' perspectives
- Week 1: Introduction and Expectations
- Week 3: Is Bayes truly the best?
- Hw1: Discuss the first hw here.
Homework
References
- "Introduction to Statistical Pattern Recognition" by K. Fukunaga_OldKiwi (This is the main reference)
- "Pattern Classification" by Duda, Hart, and Stork_OldKiwi
- "Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler_OldKiwi
- "Pattern Recognition and Neural Networks" by Brian Ripley_OldKiwi
- "Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar_OldKiwi
