1.

Record Nr.

UNINA990009892640403321

Autore

Trefethen, Lloyd N.

Titolo

Approximation theory and approximation practice / Lloyd N. Trefethen

Pubbl/distr/stampa

Philadelphia : SIAM, ©2013

ISBN

978-1-611972-39-9

Descrizione fisica

305 p. : ill. ; 25 cm

Disciplina

511.4

Locazione

DINEL

SC1

Collocazione

10 B II 839

511.4-TRE-1

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



2.

Record Nr.

UNINA9910629276103321

Autore

Mohammadzadeh Ardashir

Titolo

Modern Adaptive Fuzzy Control Systems / / by Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

3-031-17393-7

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (161 pages)

Collana

Studies in Fuzziness and Soft Computing, , 1860-0808 ; ; 421

Disciplina

629.8312

629.836

Soggetti

Computational intelligence

Automatic control

Artificial intelligence

Computational Intelligence

Control and Systems Theory

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Chapter 1: An Introduction to Fuzzy and Fuzzy Control Systems -- Chapter 2: Classification of Adaptive Fuzzy Controllers -- Chapter 3: Type-2 Fuzzy Systems -- Chapter 4: Training Interval Type-2 Fuzzy Systems Based on Error Backpropagation.

Sommario/riassunto

This book explains the basic concepts, theory and applications of fuzzy systems in control in a simple unified approach with clear ex-amples and simulations in the MATLAB programming language. Fuzzy systems, especially, type-2 neuro-fuzzy systems, are now used extensively in various engineering fields for different purposes. In plain language, this book aims to practically explain fuzzy sys-tems and different methods of training and optimizing these systems. For this purpose, type-2 neuro-fuzzy systems are first analyzed along with various methods of training and optimizing these systems through implementation in MATLAB. These systems are then em-ployed to design adaptive fuzzy controllers. The authors aim at pre-senting all the well-known



optimization methods clearly and code them in the MATLAB language.