MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT OpenCourseWare (MIT OCW) - Archived Content
  • MIT OCW Archived Courses
  • MIT OCW Archived Courses
  • View Item
  • DSpace@MIT Home
  • MIT OpenCourseWare (MIT OCW) - Archived Content
  • MIT OCW Archived Courses
  • MIT OCW Archived Courses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

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

Author(s)
Massachusetts Institute of Technology. Media Laboratory.
Thumbnail
DownloadMAS-622Fall-2000/OcwWeb/Media-Arts-and-Sciences/MAS-622Pattern-Recognition---AnalysisFall2000/CourseHome/index.htm (13.28Kb)
Alternative title
Pattern Recognition & Analysis
Terms of use
Usage Restrictions: This site (c) Massachusetts Institute of Technology 2003. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license"). The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions.
Metadata
Show full item record
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.
Date issued
2000-12
URI
http://hdl.handle.net/1721.1/41935
Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology); Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Other identifiers
MAS.622-Fall2000
local: MAS.622
local: 1.126J
local: IMSCP-MD5-4daecab298b87ed17e30c68b58fa204f
Keywords
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

Collections
  • MIT OCW Archived Courses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.