MAS.622 / 1.126J Pattern Recognition & Analysis, Fall 2000

MAS.622 / 1.126J Pattern Recognition & Analysis, Fall 2000

Fundamentals of characterizing and recognizing patterns and features of interest in numerical data. Basic tools and theory for signal understanding problems with applications to user modeling, affect recognition, speech recognition and understanding, computer vision, physiological analysis, and more...

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Bibliographic Details
Main Author: Massachusetts Institute of Technology. Media Laboratory.
Other Authors: Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Format: Learning Object
Language:en-US
Published: 2000
Subjects:
machine and human learning
unsupervised learning and clustering
non-parametric methods
Bayesian estimation
maximum likelihood
statistical classification
decision theory
physiological analysis
computer vision
peech recognition and understanding
recognition
numerical data
MAS.622
1.126J
1.126
Pattern perception
Pattern recognition systems
Online Access:http://hdl.handle.net/1721.1/41935

Internet

http://hdl.handle.net/1721.1/41935

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