Chapter1: Dimensionality Reduction Techniques.- Chapter2: Linear classifier techniques.- Chapter3: Regression techniques. Chapter4: Probabilistic supervised classifier and unsupervised clustering.- Chapter5: Computational intelligence.- Chapter6: Statistical test in pattern recognition.
E. S. Gopi is currently an Associate Professor in the Department of Electronics and Communication Engineering, National Institute of Technology Trichy. He has two decades of teaching and research experience. He has authored seven books and five book chapters. He has several papers in international journals and conferences to his credit. He is also the coordinator for the Pattern Recognition and Computational Intelligence Laboratory and the COMPSIG newsletter. His research interests include pattern recognition, signal processing, and computational intelligence. He received the “Shiksha Rattan Puraskar Award” for his meritorious services in the field of education by the India International Friendship Society. The award was presented by Dr. Bhishma Narain Singh, former Governor, Assam and Tamil Nadu, India. He also received the “Glory of India Gold Medal” by International Institute of Success Awareness. This award was presented by Shri Syed Sibtey Razi, former Governor of Jharkhand, India. He was also awarded with “Best Citizens of India 2013” by The International Publishing House.
This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques.
Presents pattern recognition and the computational intelligence using Matlab;
Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly;
Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.