COURSE SUMMARY
Course Title: 
Pattern Recognition Techniques and Algorithms
Course Code: 
15ECE331
Year Taught: 
2015
Type: 
Elective
Degree: 
Undergraduate (UG)
School: 
School of Engineering
Campus: 
Bengaluru
Chennai
Coimbatore
Amritapuri

'Pattern Recognition Techniques and Algorithms' is an elective course offered for the B. Tech. (Bachelor of Technology) in Electronics and Communication Engineering at School of Engineering, Amrita Vishwa Vidyapeetham.

Unit 1

Statistical decision making techniques: Bayes’ theorem - Multiple features - Conditionally independent features - Decision boundaries - Unequal costs of error - Estimation of error rates - Leaving one out technique - Characteristic curves.

Unit 2

Non-parametric decision making techniques: Histograms - Kernel and window estimators - Nearest neighbor classification techniques - Adaptive decision boundaries - Adaptive discriminant functions - Minimum squared error discriminant functions - Choosing a decision making technique.

Unit 3

Artificial neural networks: nets without hidden layers - Nets with hidden layers - Back propagation algorithm - Hopfield nets.

TEXTBOOKS

  1. Earl Gose, Richard Johnsonbaugh, Steve Jost, “Pattern Recognition and Image Analysis”, PHI Learning Private Ltd., New Delhi, 2009.

REFERENCES

  1. Jiawei Han, Micheline Kamber, Jian Pei, “Data Mining: Concepts and Techniques”, Third Edition, Morgan Kaufmann Publishers (Elsevier), 2011.
  2. K. P Soman, Shyam Diwakar, V. Ajay, “Insight into Data Mining: Theory and Practice”, PHI Learning Private Ltd., New Delhi, 2006.
  3. Sergios Theodoridis, Konstantinos Koutroumbas,“Pattern Recognition”, Fourth Edition, Academic Press (Elsevier), 2011.