Fuzzy Logic Matlab
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Introduction to Fuzzy Logic using MATLAB
Author: S.N. Sivanandam
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-10-28
Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Fuzzy Logic with MATLAB
Author: Godfrey H.
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2016-11-12
Fuzzy Logic Toolbox provides MATLAB functions, graphical tools, and a SimulinkR block for analyzing, designing, and simulating systems based on fuzzy logic. The product guides you through the steps of designing fuzzy inference systems. Functions are provided for many common methods, including fuzzy clustering and adaptive neurofuzzy learning. The toolbox lets you model complex system behaviors using simple logic rules, and then implement these rules in a fuzzy inference system. You can use it as a stand-alone fuzzy inference engine. Alternatively, you can use fuzzy inference blocks in Simulink and simulate the fuzzy systems within a comprehensive model of the entire dynamic system. The more important features are the next:* Specialized GUIs for building fuzzy inference systems and viewing and analyzing results* Membership functions for creating fuzzy inference systems * Support for AND, OR, and NOT logic in user-defined rules* Standard Mamdani and Sugeno-type fuzzy inference systems* Automated membership function shaping through neuroadaptive and fuzzy clustering learning techniques* Ability to embed a fuzzy inference system in a Simulink model * Ability to generate embeddable C code or stand-alone executable fuzzy inference engines
Fuzzy Logic With Matlab
Author: A. Taylor
language: en
Publisher: Createspace Independent Publishing Platform
Release Date: 2017-11-15
Fuzzy Logic Toolbox provides MATLAB functions, apps, and a Simulink block for analyzing, designing, and simulating systems based on fuzzy logic. The book guides you through the steps of designing fuzzy inference systems. Functions are provided formany common methods, including fuzzy clustering and adaptive neuro fuzzy learning.The toolbox lets you model complex system behaviors using simple logic rules, and then implement these rules in a fuzzy inference system. You can use it as a stand-alone fuzzy inference engine. Alternatively, you can use fuzzy inference blocks in Simulink and simulate the fuzzy systems within a comprehensive model of the entire dynamic system. The most important features that this Toolbox provides are the following: - Fuzzy Logic Design app for building fuzzy inference systems and viewing andanalyzing results - Membership functions for creating fuzzy inference systems - Support for AND, OR, and NOT logic in user-defined rules - Standard Mamdani and Sugeno-type fuzzy inference systems - Automated membership function shaping through neuroadaptive and fuzzy clusteringlearning techniques - Ability to embed a fuzzy inference system in a Simulink model - Ability to generate embeddable C code or stand-alone executable fuzzy inferenceengines