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[[Category:ECE662]]
 
[[Category:ECE662]]
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[[Category:pattern recognition]]
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[[Category:decision theory]]
  
= ECE 662: Statistical Pattern Recognition and Decision Making Processes =
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Click [[:Category:ECE662|here]] to view a list of all pages in the ECE662 category.
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<center><font size= 4>
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'''[[ECE662]]: Statistical Pattern Recognition and Decision Making Processes'''
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</font size>
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(cross-listed with computer science as CS662)
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</center>
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----
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----
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This course was previously developed and taught by Professor [https://engineering.purdue.edu/ECE/People/profile?resource_id=3088 Keinosuke Fukunaga].
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Since 2006, it is taught by [[user:mboutin|Prof. Boutin]] every Spring of even years.  
  
 
==Textbooks==
 
==Textbooks==
[["Introduction to Statistical Pattern Recognition" by K. Fukunaga_OldKiwi]]
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[["Introduction to Statistical Pattern Recognition" by K. Fukunaga_OldKiwi|"Introduction to Statistical Pattern Recognition" by K. Fukunaga]]
  
 
== Peer Legacy ==
 
== Peer Legacy ==
 
Share advice with future students regarding ECE662 on [[Peer_Legacy_ECE662|this page]].   
 
Share advice with future students regarding ECE662 on [[Peer_Legacy_ECE662|this page]].   
  
== Main Course Topics ==
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== Slectures and Lecture Notes ==
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*[[ECE662_Pattern_Recognition_Decision_Making_Processes_Spring2008_sLecture_collective|Spring 2008, Prof. Boutin]], notes collectively written by the students in the class.
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*[[2014_Spring_ECE_662_Boutin_Statistical_Pattern_recognition_slectures|The Boutin Lectures on Statistical Pattern Recognition]], Multilingual Slectures by Students in the Spring 2014 Class of ECE662
  
* [[About Pattern Recognition]]
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== Some Course Topics ==
 
* [[Bayes_Decision_Theory]]
 
* [[Bayes_Decision_Theory]]
* [[Discriminant Functions]]
 
 
* [[Fisher Linear Discriminant]]
 
* [[Fisher Linear Discriminant]]
* [[Bayesian Decision Theory for Normally Distributed Features]]
 
 
* [[Feature Extraction]]
 
* [[Feature Extraction]]
* [[Density Estimation]]
 
* [[Linear classifiers]]
 
 
* [[Artificial Neural Networks]]
 
* [[Artificial Neural Networks]]
 
* [[Support Vector Machines]]
 
* [[Support Vector Machines]]
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== Interesting pages in the ECE662 category ==
 
== Interesting pages in the ECE662 category ==
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*[[ECE662:Glossary_Old_Kiwi|Decision Theory Glossary]]
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*[[Bayes_Classification:_Experiments_and_Notes_OldKiwi|The effect of adding correlated features]]
 
*[[Parametric_Estimators_OldKiwi|About Parametric Estimators]]
 
*[[Parametric_Estimators_OldKiwi|About Parametric Estimators]]
 
*[[Bayes_Rate_Fallacy:_Bayes_Rules_under_Severe_Class_Imbalance|Bayes rule under severe class imbalance]]
 
*[[Bayes_Rate_Fallacy:_Bayes_Rules_under_Severe_Class_Imbalance|Bayes rule under severe class imbalance]]
 
*[[Fisher_discriminant_under_nonlinear_data|Fisher linear discriminant can be used for non-linearly separable data too!]]
 
*[[Fisher_discriminant_under_nonlinear_data|Fisher linear discriminant can be used for non-linearly separable data too!]]
 
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*[[ANN_Simulink_examples_ece662_Sp2010|A jump start on using Simulink to develop a ANN-based classifier]]
 
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*[[KNN-K_Nearest_Neighbor_OldKiwi|The K Nearest Neighbor Algorithm]]
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*[[MLE_Examples:_Binomial_and_Poisson_Distributions_OldKiwi|MLE example: binomial and poisson distributions]]
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*[[MLE_Examples:_Exponential_and_Geometric_Distributions_OldKiwi|MLE example: exponential and geometric distributions]]
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*[[Bayes_Decision_Rule_Old_Kiwi|Video illustrating the decision boundary for normally distributed features]]
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::<youtube>wzJkaATyitA</youtube>
 
== Semester/Instructor specific pages ==
 
== Semester/Instructor specific pages ==
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*[[2016_Spring_ECE_662_Boutin|Spring 2016, Prof. Boutin]]
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*[[2014_Spring_ECE_662_Boutin|Spring 2014, Prof. Boutin]]
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*[[2012_Spring_ECE_662_Boutin|Spring 2012, Prof. Boutin]]
 
*[[2010_Spring_ECE_662_mboutin|Spring 2010, Prof. Boutin]]
 
*[[2010_Spring_ECE_662_mboutin|Spring 2010, Prof. Boutin]]
 
*[[ECE662:BoutinSpring08_OldKiwi|Spring 2008, Prof. Boutin]]
 
*[[ECE662:BoutinSpring08_OldKiwi|Spring 2008, Prof. Boutin]]
  
 
==Other References==
 
==Other References==
* [["Pattern Classification" by Duda, Hart, and Stork_OldKiwi]]
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* [["Pattern Classification" by Duda, Hart, and Stork_OldKiwi|"Pattern Classification" by Duda, Hart, and Stork]]
* [["Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler_OldKiwi]]
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* [["Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler_OldKiwi|"Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler]]
* [["Pattern Recognition and Neural Networks" by Brian Ripley_OldKiwi]]
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* [["Pattern Recognition and Neural Networks" by Brian Ripley_OldKiwi|"Pattern Recognition and Neural Networks" by Brian Ripley]]
* [["Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar_OldKiwi]]
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* [["Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar_OldKiwi|"Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar]]
 
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== Related Courses ==
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Please help complete this section: which course relates to ECE662?
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[[ECE|Back to ECE]]
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[[Meta Course List|Back to Course List]]
 
[[Meta Course List|Back to Course List]]

Latest revision as of 09:07, 11 January 2016


ECE662: Statistical Pattern Recognition and Decision Making Processes

(cross-listed with computer science as CS662)



This course was previously developed and taught by Professor Keinosuke Fukunaga.

Since 2006, it is taught by Prof. Boutin every Spring of even years.

Textbooks

"Introduction to Statistical Pattern Recognition" by K. Fukunaga

Peer Legacy

Share advice with future students regarding ECE662 on this page.

Slectures and Lecture Notes

Some Course Topics

Interesting pages in the ECE662 category

Semester/Instructor specific pages

Other References


Back to ECE

Back to Course List

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