Central Library

Normal view MARC view ISBD view

Pattern Recognition and Computational Intelligence Techniques Using Matlab [electronic resource] / by E. S. Gopi.

By: Gopi, E. S [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Transactions on Computational Science and Computational Intelligence: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: XIII, 256 p. 137 illus., 127 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030222734.Subject(s): Telecommunication | Engineering mathematics | Engineering—Data processing | Signal processing | Pattern recognition systems | Data mining | Communications Engineering, Networks | Mathematical and Computational Engineering Applications | Signal, Speech and Image Processing | Automated Pattern Recognition | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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.
    average rating: 0.0 (0 votes)
No physical items for this record

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.

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.

There are no comments for this item.

Log in to your account to post a comment.