Kirjojen hintavertailu. Mukana 12 211 733 kirjaa ja 12 kauppaa.
Kirjailija
Ardashir Mohammadzadeh
Kirjat ja teokset yhdessä paikassa: 4 kirjaa, julkaisuja vuosilta 2022-2026, suosituimpien joukossa Practical Neural Networks in Python and MATLAB. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.
This book provides the fundamental approaches to designing and using type-3 fuzzy systems in real-world applications. Basic Matlab codes are provided to use type-3 fuzzy systems in a straightforward scheme. The main differences between type-3 fuzzy systems and other types are analyzed and compared. The effectiveness of type-3 fuzzy systems is analyzed and studied in various applications, such as robotics, intelligent control systems, and data science.
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.
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.
