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[[Category:ECE662Spring2010mboutin]]
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= [[ECE662]]: "Statistical Pattern Recognition and Decision Making Processes", Spring 2010 =
=[[ECE662]]: "Satistical Pattern Recognition and Decision Making Processes", Spring 2010=
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Message Area:
 
Message Area:
  
Welcome!
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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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== General Course Information ==
  
Rhea is now on [http://www.facebook.com/pages/West-Lafayette-IN/Rhea/88771959948 Facebook].
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*Instructor: [[User:Mboutin|Prof. Boutin]] a.k.a. Prof. Mimi
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*Office: MSEE342
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*Email: mboutin at purdue dot you know where
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*Class meets Tu,Th 12-13:15 in EE115
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*Office hours are listed [[Open office hours mboutin|here]]
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*[[Media:SyllabusECE662S10.pdf|Syllabus]]
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*[[OutlineECE662S10|Course Outline]]
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*Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25
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*Make up classes: Friday April 9, 16, 23, 30, 1:30-2:30, EE117.
  
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==Lecture Summaries==
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[[Lecture1ECE662S10|Lecture 1]],
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[[Lecture2ECE662S10|2]],
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[[Lecture3ECE662S10|3]]
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,[[Lecture4ECE662S10|4]]
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,[[Lecture5ECE662S10|5]]
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,[[Lecture6ECE662S10|6]]
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,[[Lecture7ECE662S10|7]]
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,[[Lecture8ECE662S10|8]]
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,[[Lecture9ECE662S10|9]]
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,[[Lecture10ECE662S10|10]]
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,[[Lecture11ECE662S10|11]]
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,[[Lecture12ECE662S10|12]]
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,[[Lecture13ECE662S10|13]]
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,[[Lecture14ECE662S10|14]]
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,[[Lecture15ECE662S10|15]]
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,[[Lecture16ECE662S10|16]]
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,[[Lecture17ECE662S10|17]]
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,[[Lecture18ECE662S10|18]]
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,[[Lecture19ECE662S10|19]]
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,[[Lecture20ECE662S10|20]]
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,[[Lecture21ECE662S10|21]]
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,[[Lecture22ECE662S10|22]]
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,[[Lecture23ECE662S10|23]]
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,[[Lecture24ECE662S10|24]]
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,[[Lecture25ECE662S10|25]]
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,[[Lecture26ECE662S10|26]]
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,[[Lecture27ECE662S10|27]]
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,[[Lecture28ECE662S10|28]]
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,[[Lecture29ECE662S10|29]].
  
==General Course Information==
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== Links and Material Used in Class ==
* Instructor: [[User:mboutin|Prof. Boutin]] a.k.a. Prof. Mimi
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* Office: MSEE342
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* Email: mboutin at purdue dot you know where
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* Class meets Tu,Th 12-13:15 in EE115
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* Office hours are listed [[Open_office_hours_mboutin|here]]
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*[[Media:syllabusECE662S10.pdf|Syllabus]]
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* Class cancellation: Jan 19, Jan 21, Feb 23, Feb 25
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* Make up classes: to be announced. Please list the times when you cannot meet [[schedule_surveyECE662S09|here]]
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==Class related material==
 
 
*[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 ==
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== Discussions and Students' perspectives ==
*[[ECE662_topic1_discussions|Introduction and Expectations]]
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*[[ECE662_topic2_discussions|Is Bayes truly the best?]]
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*[[ECE662_topic3_discussions|Central Limit Theorem illustrations]]
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*[[ECE662_hw1_discussions|Hw1: Discuss the first hw here.]]
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==Homework==
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*[[ECE662 topic1 discussions|Introduction and Expectations]]
* [[hw0_ECE662Spring2010|HW0 - getting ready]]  
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*[[ECE662 topic2 discussions|Is Bayes truly the best?]]  
*[[hw1_ECE662Spring2010|HW1- Bayes rule for normally distributed features]]
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*[[ECE662 topic3 discussions|Central Limit Theorem illustrations]]
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*[[ECE662 hw1 discussions|Hw1: Discuss the first hw here.]]
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*[[EE662Sp10Semimetric|Distance Functions Where Triangle Inequality Doesn't Hold]]
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*[[EE662Sp10AbstarctAlgebra|Group Theory Background for 3-25-10 and 3-30-10 Lectures]]
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*[[ECE662 hw2 discussions|Hw2: Discuss the second hw here.]]
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*[[ECE662 hw3 discussions|Hw3: Discuss the third hw here.]]
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*[[ECE662 topic8 discussions|Linear Perceptron classifier in Batch mode]]
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*[[Bayes_Rate_Fallacy:_Bayes_Rules_under_Severe_Class_Imbalance|Bayes rule under severe class imbalance]]
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*[[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]]
  
==References==
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== Feedback  ==
  
* [["Introduction to Statistical Pattern Recognition" by K. Fukunaga_OldKiwi]] (This is the main reference)
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*[[Star feedbackECE662S2010|Stars for Rhea participation]] <span style="text-decoration: blink;"> New! </span>
* [["Pattern Classification" by Duda, Hart, and Stork_OldKiwi]]
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*[[FavoritedecisionECE662S10|Student Poll: What is your favorite decision method?]]
* [["Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler_OldKiwi]]
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* [["Pattern Recognition and Neural Networks" by Brian Ripley_OldKiwi]]
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* [["Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar_OldKiwi]]
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== Homework ==
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*[[Hw0 ECE662Spring2010|HW0 - getting ready]]
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*[[Hw1 ECE662Spring2010|HW1- Bayes rule for normally distributed features]]
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*[[Hw2 ECE662Spring2010|HW2- Bayes rule using parametric density estimation]]
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*[[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)
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*[["Pattern Classification" by Duda, Hart, and Stork OldKiwi]]
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*[["Pattern Recognition: A Statistical Approach" by P.A. Devijver and J.V. Kittler OldKiwi]]
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*[["Pattern Recognition and Neural Networks" by Brian Ripley OldKiwi]]
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*[["Introduction to Data Mining" by P-N Tan, M. Steinbach and V. Kumar OldKiwi]]
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== Class Notes ==
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*[[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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[[Course List|Back to course list]]
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[[Course List|Back to course list]]
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[[Category:ECE662Spring2010mboutin]]

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

Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010