Gopi E. Pattern Recognition and Computational..Using Matlab 2019

Textbook in PDF format

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.
Artificial Neural Network is a biologically inspired algorithm, mimicking the working of the brain. The most often used mathematical model of the brain is the back propagation feed-forward neural network. It consists of layered architecture. Each layer consists of neurons. Every neuron in the input layer is connected to every neuron in the hidden layer. Furthermore, every neuron in the hidden layer is connected to every neuron in the output layer. This is used for (a) regression model, (b) two-class classification model, and (c) multi-class classification model.
- 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