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18-794 Pattern Recognition Theory

Department:Electrical & Comp. Eng.
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Decision theory, parameter estimation, density estimation, non-parametric techniques, supervised learning, linear discriminant functions, clustering, unsupervised learning, artificial neural networks, feature extraction, support vector machines, and pattern recognition applications (e.g., face recognition, fingerprint recognition, automatic target recognition, etc.). 4 hrs. lec. Prerequisites: 36-217, or equivalent introductory probability theory and random variables course and an introductory linear algebra course.

  Popularity index
Rank for this semester:#429
Rank in this department:#28

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  Spring 2005 times

Sec Time Day Instructor Location  
A 9:30 - 11:20 am T Savvides, Bhagavatula DH A310 Add course to my schedule
R Savvides, Bhagavatula DH A310

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