{"id":577,"date":"2016-07-24T12:59:24","date_gmt":"2016-07-24T12:59:24","guid":{"rendered":"http:\/\/www.inspirenignite.com\/jntuk\/?p=577"},"modified":"2016-08-07T14:15:37","modified_gmt":"2016-08-07T14:15:37","slug":"jntuk-b-tech-pattern-recognition-elective-iii-for-r13-batch","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/jntuk\/jntuk-b-tech-pattern-recognition-elective-iii-for-r13-batch\/","title":{"rendered":"JNTUK B.Tech Pattern Recognition (Elective \u2013 III) for R13 Batch."},"content":{"rendered":"<p>JNTUK B.Tech Pattern Recognition (Elective \u2013 III) gives you detail information of Pattern Recognition (Elective \u2013 III) R13 syllabus It will be help full to understand you complete curriculum of the year.<\/p><div class=\"a9916ad81d5189659b0bfae0b37c143c\" data-index=\"1\" style=\"float: none; margin:10px 0 10px 0; text-align:center;\">\n<ins class=\"adsbygoogle\"\r\n     style=\"display:block; text-align:center;\"\r\n     data-ad-layout=\"in-article\"\r\n     data-ad-format=\"fluid\"\r\n     data-ad-client=\"ca-pub-1181153414625576\"\r\n     data-ad-slot=\"9648548092\"><\/ins>\r\n<script>\r\n     (adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script>\n<\/div>\n\n<p><strong>Course Objectives<\/strong><br \/>\nThe course is designed to introduce students to theoretical concepts and practical<br \/>\nissues associated with pattern recognition<\/p>\n<p><strong>Course Outcomes<\/strong><br \/>\nDesign systems and algorithms for pattern recognition (signal classification), with focus on sequences of patterns that are analyzed using, e.g., hidden Markov models (HMM),<\/p>\n<ul>\n<li>Analyse classification problems probabilistically and estimate classifier performance,<\/li>\n<li>Understand and analyse methods for automatic training of classification systems,<\/li>\n<li>Apply Maximum-likelihood parameter estimation in relatively complex probabilistic models, such as mixture density models and hidden Markov models,<\/li>\n<li>Understand the principles of Bayesian parameter estimation and apply them in relatively simple probabilistic models<\/li>\n<\/ul>\n<p><strong>Syllabus<\/strong><\/p>\n<p><strong>UNIT-I: Introduction:<\/strong> Machine perception, pattern recognition example, pattern recognition systems, the Design cycle, learning and adaptation<br \/>\nBayesian Decision Theory: Introduction, continuous features \u2013 two categories classifications, minimum error-rate classification-zero\u2013one loss function, classifiers, discriminant functions, and decision surfaces.<\/p>\n<p><strong>UNIT-II: Normal density:<\/strong> Univariate and multivariate density, discriminant functions for the normal Density different cases, Bayes decision theory \u2013 discrete features, compound Bayesian decision theory and context<\/p>\n<p><strong>UNIT-III : Maximum likelihood and Bayesian parameter estimation:<\/strong> Introduction, maximum likelihood Estimation, Bayesian estimation, Bayesian parameter estimation\u2013Gaussian case<\/p>\n<p><strong>UNIT-IV : Un-supervised learning and clustering<\/strong>: Introduction, mixture densities and identifiability, maximum likelihood estimates, application to normal mixtures, K-means clustering. Date description and clustering \u2013 similarity measures, criteria function for clustering<\/p>\n<p><strong>UNIT-V : Pattern recognition using discrete hidden Markov models:<\/strong> Discrete-time Markov process, Extensions to hidden Markov models, three basic problems of HMMs, types of HMMs<\/p>\n<p><strong>UNIT-VI : Continuous hidden Markov models :<\/strong> Continuous observation densities, multiple mixtures per state, speech recognition applications.<\/p>\n<p><strong>Text Books<\/strong><\/p>\n<ul>\n<li>Pattern classifications, Richard O. Duda, Peter E. Hart, David G. Stroke. Wiley student edition, Second Edition.<\/li>\n<li>Pattern Recognition, An Introduction, V Susheela Devi, M Narsimha Murthy, Universiy Press<\/li>\n<\/ul>\n<p>For more information about all JNTU updates please stay connected to us on FB and don\u2019t hesitate to ask any questions in the comment.<\/p>\n<div class=\"a9916ad81d5189659b0bfae0b37c143c\" data-index=\"2\" style=\"float: none; margin:10px 0 10px 0; text-align:center;\">\n<ins class=\"adsbygoogle\"\r\n     style=\"display:block; text-align:center;\"\r\n     data-ad-layout=\"in-article\"\r\n     data-ad-format=\"fluid\"\r\n     data-ad-client=\"ca-pub-1181153414625576\"\r\n     data-ad-slot=\"8060844699\"><\/ins>\r\n<script>\r\n     (adsbygoogle = window.adsbygoogle || []).push({});\r\n<\/script>\n<\/div>\n\n<div style=\"font-size: 0px; height: 0px; line-height: 0px; margin: 0; padding: 0; clear: both;\"><\/div>","protected":false},"excerpt":{"rendered":"<p>JNTUK B.Tech Pattern Recognition (Elective \u2013 III) gives you detail information of Pattern Recognition (Elective \u2013 III) R13 syllabus It will be help full to understand you complete curriculum of [&hellip;]<\/p>\n","protected":false},"author":2259,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[2],"tags":[],"class_list":["post-577","post","type-post","status-publish","format-standard","hentry","category-syllabus"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/posts\/577","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/users\/2259"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/comments?post=577"}],"version-history":[{"count":1,"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/posts\/577\/revisions"}],"predecessor-version":[{"id":578,"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/posts\/577\/revisions\/578"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/media?parent=577"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/categories?post=577"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuk\/wp-json\/wp\/v2\/tags?post=577"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}