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= [[ECE662]]: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010 =
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= [[ECE662]]: "Statistical Pattern Recognition and Decision Making Processes", Spring 2010 =
 
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<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;">
 
Message Area:
 
Message Area:
  
The dates for the make classes are Friday April 9,16,23. Time is 1:30-2:30. Location  EE117.
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If you are interested in robotics and vision, there is a new course for you next Fall: [[2010_Fall_IE_590_Wachs| IE 590 "Robotics and Machine Vision"]]
 
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</div>  
 
== General Course Information ==
 
== General Course Information ==
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*[[OutlineECE662S10|Course Outline]]  
 
*[[OutlineECE662S10|Course Outline]]  
 
*Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25  
 
*Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25  
*Make up classes: Friday April 9, 16, 23, 1:30-2:30, EE117.
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*Make up classes: Friday April 9, 16, 23, 30, 1:30-2:30, EE117.
  
==Lectures in more Details==
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==Lecture Summaries==
*[[Lecture1ECE662S10|Lecture 1]]
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[[Lecture1ECE662S10|Lecture 1]],
*[[Lecture2ECE662S10|Lecture 2]]
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[[Lecture2ECE662S10|2]],
*[[Lecture3ECE662S10|Lecture 3]]
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[[Lecture3ECE662S10|3]]
*[[Lecture4ECE662S10|Lecture 4]]
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,[[Lecture4ECE662S10|4]]
*[[Lecture5ECE662S10|Lecture 5]]
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,[[Lecture5ECE662S10|5]]
*[[Lecture6ECE662S10|Lecture 6]]
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,[[Lecture6ECE662S10|6]]
*[[Lecture7ECE662S10|Lecture 7]]
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,[[Lecture7ECE662S10|7]]
*[[Lecture8ECE662S10|Lecture 8]]
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,[[Lecture8ECE662S10|8]]
*[[Lecture9ECE662S10|Lecture 9]]
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,[[Lecture9ECE662S10|9]]
*[[Lecture10ECE662S10|Lecture 10]]
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,[[Lecture10ECE662S10|10]]
*[[Lecture11ECE662S10|Lecture 11]]
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,[[Lecture11ECE662S10|11]]
*[[Lecture12ECE662S10|Lecture 12]]
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,[[Lecture12ECE662S10|12]]
*[[Lecture13ECE662S10|Lecture 13]]
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,[[Lecture13ECE662S10|13]]
*[[Lecture14ECE662S10|Lecture 14]]
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,[[Lecture14ECE662S10|14]]
*[[Lecture15ECE662S10|Lecture 15]]
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,[[Lecture15ECE662S10|15]]
*[[Lecture16ECE662S10|Lecture 16]]
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,[[Lecture16ECE662S10|16]]
*[[Lecture17ECE662S10|Lecture 17]]
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,[[Lecture17ECE662S10|17]]
*[[Lecture18ECE662S10|Lecture 18]]
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,[[Lecture18ECE662S10|18]]
*[[Lecture19ECE662S10|Lecture 19]]
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,[[Lecture19ECE662S10|19]]
*[[Lecture20ECE662S10|Lecture 20]]
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,[[Lecture20ECE662S10|20]]
*[[Lecture21ECE662S10|Lecture 21]]
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,[[Lecture21ECE662S10|21]]
*[[Lecture22ECE662S10|Lecture 22]]
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,[[Lecture22ECE662S10|22]]
*[[Lecture23ECE662S10|Lecture 23]]
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,[[Lecture23ECE662S10|23]]
*[[Lecture24ECE662S10|Lecture 24]]
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,[[Lecture24ECE662S10|24]]
*[[Lecture25ECE662S10|Lecture 25]]
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,[[Lecture25ECE662S10|25]]
*[[Lecture26ECE662S10|Lecture 26]]
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,[[Lecture26ECE662S10|26]]
*[[Lecture27ECE662S10|Lecture 27]]
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,[[Lecture27ECE662S10|27]]
*[[Lecture28ECE662S10|Lecture 28]]
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,[[Lecture28ECE662S10|28]]
*[[Lecture29ECE662S10|Lecture 29]]
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,[[Lecture29ECE662S10|29]].
*[[Lecture30ECE662S10|Lecture 30]]
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== Links and Material Used in Class ==
 
== Links and Material Used in Class ==
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*[[ECE662 topic8 discussions|Linear Perceptron classifier in Batch mode]]
 
*[[ECE662 topic8 discussions|Linear Perceptron classifier in Batch mode]]
 
*[[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 in non linearly separable data]]
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*[[One_class_svm|One-Class Support Vector Machines for Anomaly Detection]]
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*[[EE662Sp10_HiddenMarkovModel|Intro to Hidden Markov Model]]
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*[[ANN_Simulink_examples_ece662_Sp2010|ANN Jump Start: Using MATLAB Simulink to train a network]]
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== Feedback  ==
 
== Feedback  ==
  
 
*[[Star feedbackECE662S2010|Stars for Rhea participation]] <span style="text-decoration: blink;"> New! </span>
 
*[[Star feedbackECE662S2010|Stars for Rhea participation]] <span style="text-decoration: blink;"> New! </span>
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*[[FavoritedecisionECE662S10|Student Poll: What is your favorite decision method?]]
  
 
== Homework ==
 
== Homework ==
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== Class Notes ==
 
== Class Notes ==
 
 
*[[ECE662Sp10_MakeupLectureNotes01|Makeup Lecture #1, 9 April 2010]]
 
*[[ECE662Sp10_MakeupLectureNotes01|Makeup Lecture #1, 9 April 2010]]
 
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*[[Noteslecture8ECE662S10|Lecture 8]]
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*[[Noteslecture11ECE662S10|Lecture 11]]
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*[[Noteslecture20ECE662S10|Lecture 20, Thursday April 8, 2010]]
 
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Latest revision as of 12:24, 25 June 2010



ECE662: "Statistical Pattern Recognition and Decision Making Processes", Spring 2010

Message Area:

If you are interested in robotics and vision, there is a new course for you next Fall: IE 590 "Robotics and Machine Vision"

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: Friday April 9, 16, 23, 30, 1:30-2:30, EE117.

Lecture Summaries

Lecture 1, 2, 3 ,4 ,5 ,6 ,7 ,8 ,9 ,10 ,11 ,12 ,13 ,14 ,15 ,16 ,17 ,18 ,19 ,20 ,21 ,22 ,23 ,24 ,25 ,26 ,27 ,28 ,29.

Links and Material Used in Class

Discussions and Students' perspectives

Feedback

Homework

References

Class Notes


Back to course list

Alumni Liaison

Basic linear algebra uncovers and clarifies very important geometry and algebra.

Dr. Paul Garrett