12 units
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 and senior or graduate standing.
Last updated on March 20, 2007
Signal Processing and Communications
Signals and Systems
S10
S09, S08, S07, S05, S04, S03, S01, S99
Please note that the course history information is incomplete and/or may reflect different courses offered under the same course number.