{"id":8404,"date":"2019-12-15T03:55:05","date_gmt":"2019-12-15T03:55:05","guid":{"rendered":"https:\/\/www.inspirenignite.com\/vtu\/pattern-recognition-telecom-7th-sem-syllabus-for-vtu-be-2017-scheme-professional-elective-4\/"},"modified":"2019-12-15T03:55:05","modified_gmt":"2019-12-15T03:55:05","slug":"pattern-recognition-telecom-7th-sem-syllabus-for-vtu-be-2017-scheme-professional-elective-4","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/vtu\/pattern-recognition-telecom-7th-sem-syllabus-for-vtu-be-2017-scheme-professional-elective-4\/","title":{"rendered":"Pattern Recognition Telecom 7th Sem Syllabus for VTU BE 2017 Scheme (Professional Elective-4)"},"content":{"rendered":"<p>Pattern Recognition detail syllabus for Telecommunication Engineering (Telecom), 2017 scheme is taken from <a href=\"https:\/\/vtu.ac.in\/b-e-scheme-syllabus\/\" target=\"_blank\" rel=\"noopener\">VTU<\/a> official website and presented for VTU students. The course code (17EC753), and for exam duration, Teaching Hr\/week, Practical Hr\/week, Total Marks, internal marks, theory marks, duration and credits do visit complete sem subjects post given below.<\/p>\n<p>For all other telecom 7th sem syllabus for be 2017 scheme vtu you can visit <a href=\"..\/telecom-7th-sem-syllabus-for-be-2017-scheme-vtu\">Telecom 7th Sem syllabus for BE 2017 Scheme VTU Subjects<\/a>. For all other Professional Elective-4 subjects do refer to <a href=\"..\/professional-elective-4-telecom-7th-sem-syllabus-for-vtu-be-2017-scheme\">Professional Elective-4<\/a>. The detail syllabus for pattern recognition is as follows.<\/p>\n<p><h4>Course Objectives:<\/h4>\n<p> The objectives of this course are to:<\/p>\n<ul>\n<li>Introduce mathematical tools needed for Pattern Recognition<\/li>\n<li>Impart knowledge about the fundamentals of Pattern Recognition.<\/li>\n<li>Provide knowledge of recognition, decision making and statistical learning problems<\/li>\n<li>Introduce parametric and non-parametric techniques, supervised learning and clustering concepts of pattern recognition<\/li>\n<\/ul>\n<p><h4>Module 1<br \/>\nFor complete syllabus and results, class timetable and more pls <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a>. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.<\/p>\n<p><h4>Module 2<br \/>\n<\/h4>\n<p>Data Transformation and Dimensionality Reduction: Introduction, Basis Vectors, The Karhunen Loeve (KL) Transformation, Singular Value Decomposition, Independent Component Analysis (Introduction only). Nonlinear Dimensionality Reduction, Kernel PCA.\n<\/p>\n<p><h4>Module 3<br \/>\n<\/h4>\n<p>Estimation of Unknown Probability Density Functions: Maximum Likelihood Parameter Estimation, Maximum a Posteriori Probability estimation, Bayesian Interference, Maximum Entropy Estimation, Mixture Models, Naive-Bayes Classifier, The Nearest Neighbor Rule.\n<\/p>\n<p><h4>Module 4<br \/>\nFor complete syllabus and results, class timetable and more pls <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a>. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.<\/p>\n<p><h4>Module 5<br \/>\n<\/h4>\n<p>Nonlinear Classifiers: The XOR Problem, The two Layer Perceptron, Three Layer Perceptron, Back propagation Algorithm, Basic Concepts of Clustering, Introduction to Clustering , Proximity Measures.\n<\/p>\n<p><h4>Course Outcomes:<\/h4>\n<p> At the end of the course, students will be able to:<\/p>\n<ul>\n<li>Identify areas where Pattern Recognition and Machine Learning can offer a solution.<\/li>\n<li>Describe the strength and limitations of some techniques used in computational Machine Learning for classification, regression and density estimation problems<\/li>\n<li>Describe genetic algorithms, validation methods and sampling techniques<\/li>\n<li>Describe and model data to solve problems in regression and classification<\/li>\n<li>Implement learning algorithms for supervised tasks<\/li>\n<\/ul>\n<p><h4>Text Books:<\/h4>\n<p>Pattern Recognition: Sergios Theodoridis, Konstantinos Koutroumbas, Elsevier India Pvt. Ltd (Paper Back), 4th edition.\n<\/p>\n<p><h4>Reference Books:<\/h4>\n<ol>\n<li>The Elements of Statistical Learning: Trevor Hastie, Springer-Verlag New York, LLC (Paper Back), 2009.<\/li>\n<li>Pattern Classification: Richard O. Duda, Peter E. Hart, David G. Stork. John Wiley &amp; Sons, 2012.<\/li>\n<li>Pattern Recognition and Image Analysis Earl Gose: Richard Johnsonbaugh, Steve Jost, ePub eBook.<\/li>\n<\/li>\n<\/ol>\n<p>For detail syllabus of all other subjects of BE Telecom, 2017 regulation do visit <a href=\"..\/category\/telecom+7th-sem\">Telecom 7th Sem syllabus for 2017 Regulation<\/a>.<\/p>\n<p>Dont forget to <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a> for latest syllabus and results, class timetable and more.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pattern Recognition detail syllabus for Telecommunication Engineering (Telecom), 2017 scheme is taken from VTU official website and presented for VTU students. The course code (17EC753), and for exam duration, Teaching [&hellip;]<\/p>\n","protected":false},"author":2298,"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":[47],"tags":[],"class_list":["post-8404","post","type-post","status-publish","format-standard","hentry","category-telecom"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/posts\/8404","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/users\/2298"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/comments?post=8404"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/posts\/8404\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/media?parent=8404"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/categories?post=8404"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/vtu\/wp-json\/wp\/v2\/tags?post=8404"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}