MAS.622 / 1.126J Pattern Recognition & Analysis, Fall 2000
Name
MAS-622Fall-2000/OcwWeb/Media-Arts-and-Sciences/MAS-622Pattern-Recognition---AnalysisFall2000/CourseHome/index.htm
Size
13.28 KB
Format
HTML
Checksum (MD5)
9017407fe2fd15c06e8fcff70e330aa5
Author(s)
Massachusetts Institute of Technology. Media Laboratory.
Alternative Title
Pattern Recognition & Analysis
Date Issued
December 2000
Abstract
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. Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non-parametric methods, unsupervised learning and clustering. Additional topics on machine and human learning from active research.
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
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Persistent DSpace Link
