Department of Electrical Engineering, National Taipei University of Technology find us on facebook(將另開視窗)
Search this site | set the webpage to BLUE style set the webpage to ORANGE style set the webpage to GREEN style set the webpage to PURPLE style set the webpage to GRAY style ENLARGE the webpage | Site Map | Home | 中文(Chinese)
Home > Programs > Course Description > Pattern Recognition
::: Pattern Recognition 3 credit 3 hours
Topics that are covered in the course include: " Bayesian decision theory: the theoretical statistical basis for recognition based on Bayes theorem from probability " Maximum-likelihood and Bayesian parameter estimation: parameters of probability density functions " Nonparametric techniques: Parzen window, k-nearest neighbor " Linear discriminant functions: gradient descent, relaxation, minimum squared-error procedures such as LMS, and support vector machines " Algorithm-independent machine learning " Unsupervised learning and clustering The course is quite mathematical. Students enrolling this class are expected to have a good understanding of probability and random variables, both one-dimensional and multi-dimensional, and a good background in linear algebra as well as calculus. Some of the necessary math will be reviewed at the beginning of the course, but it is only a quick review, not a math course. Grades will be based on homework, tests, and small computer projects.
Copyright © 2020 Department of Electrical Engineering, Taipei Tech. All Rights Reserved.
Address: No. 1, Sec. 3, Chung-Hsiao E. Rd., Taipei 106, Taiwan, Republic of China
Tel:+886-2-27712171 Ext.2100 Fax:+886-2-27317187
1855841 Visits since May 26, 2003