1.

Record Nr.

UNINA9910366621503321

Autore

Gopi E. S

Titolo

Pattern Recognition and Computational Intelligence Techniques Using Matlab / / by E. S. Gopi

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020

ISBN

3-030-22273-X

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (263 pages)

Collana

Transactions on Computational Science and Computational Intelligence, , 2569-7072

Disciplina

006.4

Soggetti

Electrical engineering

Applied mathematics

Engineering mathematics

Signal processing

Image processing

Speech processing systems

Pattern perception

Data mining

Communications Engineering, Networks

Mathematical and Computational Engineering

Signal, Image and Speech Processing

Pattern Recognition

Data Mining and Knowledge Discovery

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

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.

Sommario/riassunto

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.