BME

BM5001: Pattern Recognition and Neural Networks Syllabus for Biomedical 8th Sem 2019 Regulation Anna University (Professional Elective-VII)

Pattern Recognition and Neural Networks detailed syllabus for Biomedical Engineering (Biomedical) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the Biomedical students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Biomedical Engineering 8th Sem scheme and its subjects, do visit Biomedical 8th Sem 2019 regulation scheme. For Professional Elective-VII scheme and its subjects refer to Biomedical Professional Elective-VII syllabus scheme. The detailed syllabus of pattern recognition and neural networks is as follows.

Pattern Recognition and Neural Networks

Course Objective:

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
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Get it on Google Play.

Unit I

Supervised Learning
Overview of Pattern recognition, Types of Pattern recognition, Parametric and Nonparametric approach, Bayesian classifier, Discriminant function, non-parametric density estimation, histograms, kernels, window estimators, k- nearest neighbor classifier, estimation of error rates.

Unit II

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
Get it on Google Play.

Unit III

Introduction To Neural Network
Elementary neurophysiology and biological neural network -Artificial neural network -Architecture, biases and thresholds, Hebb net, Perceptron, Adaline and Madaline.

Unit IV

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
Get it on Google Play.

Unit V

Neural Networks Based On Competition
Kohonen Self organizing map, Learning Vector Quantisation, Counter Propagation network, Case studies.

Course Outcome:

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
Get it on Google Play.

Text Books:

  1. Duda R.O, Hart P.G, “Pattern Classification and scene analysis””, Wiley Edition, 2000.
  2. Earl Gose, Richard Johnsonbaugh Steve Jost, “Pattern Recognition and Image Analysis”, Prentice Hall of India Pvt Ltd., New Delhi,1999.
  3. Freeman J. A., and Skapura B.M, “Neural networks, algorithms, applications and programming techniques”, Addison- Wesley,2003

References:

  1. Hagan, Demuth and Beale, “Neural Network Design””, Vikas Publishing House Pvt Ltd., New Delhi, 2002.
  2. Robert Schalkoff, “Pattern recognition, Statistical, Structural and neural approaches”, John Wiley and Sons (Asia) Pvt Ltd., Singapore, 2005.
  3. Laurene Fausett, “Fundamentals of Neural Networks- Architectures, Algorithms and Application”, Prentice Hall, 1994.

For detailed syllabus of all the other subjects of Biomedical Engineering 8th Sem, visit Biomedical 8th Sem subject syllabuses for 2019 regulation.

For all Biomedical Engineering results, visit Anna University Biomedical all semester results direct link.

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