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| − | + | = [[ECE662]]: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010 = | |
| − | =[[ECE662]]: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010= | + | <div style="border-style: solid; border-color: rgb(68, 68, 136) rgb(68, 68, 136) rgb(68, 68, 136) rgb(51, 51, 136); border-width: 1px 1px 1px 4px; margin: auto; padding: 2em; background: rgb(238, 238, 255) none repeat scroll 0% 0%; -moz-background-clip: -moz-initial; -moz-background-origin: -moz-initial; -moz-background-inline-policy: -moz-initial; width: 30em; text-align: center;"> |
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Message Area: | Message Area: | ||
| − | + | Four make up classes have been scheduled in class today. The dates are Friday April 9,16,23, 30. Time is 1:30-2:30. Location to be announced. | |
| − | + | </div> | |
| + | == General Course Information == | ||
| − | + | *Instructor: [[User:Mboutin|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 [[Open office hours mboutin|here]] | ||
| + | *[[Media:SyllabusECE662S10.pdf|Syllabus]] | ||
| + | *[[OutlineECE662S10|Course Outline]] | ||
| + | *Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25 | ||
| + | *Make up classes: 1:30-2:30, Friday April 9, 16, 23, 30. [[Schedule surveyECE662S09|Schedule surveyECE662S09]] | ||
| − | == | + | == Links and Material Used in Class == |
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*[http://www.statisticalengineering.com/central_limit_theorem.htm Illustration of Central Limit Theorem with uniform distrribution] | *[http://www.statisticalengineering.com/central_limit_theorem.htm Illustration of Central Limit Theorem with uniform distrribution] | ||
| − | == Discussions and Students' perspectives == | + | == Discussions and Students' perspectives == |
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| − | + | *[[ECE662 topic1 discussions|Introduction and Expectations]] | |
| − | *[[ | + | *[[ECE662 topic2 discussions|Is Bayes truly the best?]] |
| + | *[[ECE662 topic3 discussions|Central Limit Theorem illustrations]] | ||
| + | *[[ECE662 hw1 discussions|Hw1: Discuss the first hw here.]] | ||
| + | *[[EE662Sp10Semimetric|Distance Functions Where Triangle Inequality Doesn't Hold]] | ||
| + | *[[EE662Sp10AbstarctAlgebra|Group Theory Background for 3-25-10 and 3-30-10 Lectures]] | ||
| + | *[[ECE662 hw2 discussions|Hw2: Discuss the first hw here.]] | ||
| + | *[[ECE662 hw3 discussions|Hw3: Discuss the first hw here.]] | ||
| − | == | + | == Feedback == |
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| − | = | + | *[[Star feedbackECE662S2010|Stars for Rhea participation]] <span style="text-decoration: blink;"> New! </span> |
| − | * [["Introduction to Statistical Pattern Recognition" by K. | + | == Homework == |
| − | * [["Pattern Classification" by Duda, Hart, and | + | |
| − | * [["Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. | + | *[[Hw0 ECE662Spring2010|HW0 - getting ready]] |
| − | * [["Pattern Recognition and Neural Networks" by Brian | + | *[[Hw1 ECE662Spring2010|HW1- Bayes rule for normally distributed features]] |
| − | * [["Introduction to Data Mining" by P-N Tan, M. Steinbach and V. | + | *[[Hw2 ECE662Spring2010|HW2- Bayes rule using parametric density estimation]] |
| + | *[[Hw3 ECE662Spring2010|HW3- Bayes rule using non-parametric density estimation]] | ||
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| + | == References == | ||
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| + | *[["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]] | ||
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| − | [[Course List|Back to course list]] | + | |
| + | [[Course List|Back to course list]] | ||
| + | |||
| + | [[Category:ECE662Spring2010mboutin]] | ||
Revision as of 08:59, 6 April 2010
Contents
ECE662: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010
Message Area:
Four make up classes have been scheduled in class today. The dates are Friday April 9,16,23, 30. Time is 1:30-2:30. Location to be announced.
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
- Course Outline
- Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25
- Make up classes: 1:30-2:30, Friday April 9, 16, 23, 30. Schedule surveyECE662S09
Links and Material Used in Class
Discussions and Students' perspectives
- Introduction and Expectations
- Is Bayes truly the best?
- Central Limit Theorem illustrations
- Hw1: Discuss the first hw here.
- Distance Functions Where Triangle Inequality Doesn't Hold
- Group Theory Background for 3-25-10 and 3-30-10 Lectures
- Hw2: Discuss the first hw here.
- Hw3: Discuss the first hw here.
Feedback
Homework
- HW0 - getting ready
- HW1- Bayes rule for normally distributed features
- HW2- Bayes rule using parametric density estimation
- HW3- Bayes rule using non-parametric density estimation
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
