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Neuro Fuzzy And Soft Computing | By Jyh-Shing Roger Jang | Revised Edition | Pearson Publication ( English Medium )
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568-725 |
Neuro Fuzzy And Soft Computing | By Jyh-Shing Roger Jang | Revised Edition | Pearson Publication ( English Medium ).
🔍 Book Description
This book is a comprehensive, interdisciplinary guide that combines fuzzy logic, neural networks, genetic algorithms, and probabilistic reasoning into a unified soft computing framework. The text is designed to provide a deep understanding of how these computational techniques work individually and in combination.
The authors place special emphasis on Adaptive Neuro-Fuzzy Inference Systems (ANFIS), enabling readers to learn how to implement neuro-fuzzy models using real-world data. With numerous MATLAB simulations, examples, and exercises, this book is ideal for graduate-level students, researchers, and engineers working in fields like machine learning, artificial intelligence, control systems, and data-driven modeling.
✨ Key Features
Comprehensive Coverage
Covers the fundamentals of fuzzy systems, neural networks, genetic algorithms, and their integration.
ANFIS Framework
Deep insights into Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and how they can model complex functions.
Hands-on MATLAB Exercises
Includes MATLAB code and simulation results for better visualization and practice.
Real-world Applications
Examples span across control systems, decision-making, pattern recognition, and industrial modeling.
Unified Soft Computing Approach
Explains how different AI methods can be hybridized to solve complex nonlinear problems.
Well-structured Learning Path
Includes summaries, solved examples, conceptual questions, and exercises after each chapter.
Interdisciplinary Utility
Useful for students and professionals in electrical engineering, computer science, robotics, and applied AI.
Authoritative Reference
Co-authored by Roger Jang, known for introducing the ANFIS model and widely respected in AI and soft computing.
SKU / BOOK Code: | Prsn-Nero-Fuzy-&-Soft-Comptng-(E) |
Publisher: | Pearson Publication |
Author: | Jyh-Shing Roger Jang |
Binding Type: | Paperback |
No. of Pages: | 640 |
ISBN-10: | 9332549885 |
ISBN-13: | 978-9332549883 |
Edition: | Revised Edition |
Language: | English Medium |
Publish Year: | 2025-06 |
Weight (g): | 2500 |
Product Condition: | New |
Reading Age: | Above 10 Years |
Country of Origin: | India |
Genre: | Textbooks & Study Guides |
Manufacturer: | Pearson Publication |
Importer: | Pearson Publication |
Packer: | Fullfilled by Supplier |
Neuro Fuzzy And Soft Computing | By Jyh-Shing Roger Jang | Revised Edition | Pearson Publication ( English Medium ).
🔍 Book Description
This book is a comprehensive, interdisciplinary guide that combines fuzzy logic, neural networks, genetic algorithms, and probabilistic reasoning into a unified soft computing framework. The text is designed to provide a deep understanding of how these computational techniques work individually and in combination.
The authors place special emphasis on Adaptive Neuro-Fuzzy Inference Systems (ANFIS), enabling readers to learn how to implement neuro-fuzzy models using real-world data. With numerous MATLAB simulations, examples, and exercises, this book is ideal for graduate-level students, researchers, and engineers working in fields like machine learning, artificial intelligence, control systems, and data-driven modeling.
✨ Key Features
Comprehensive Coverage
Covers the fundamentals of fuzzy systems, neural networks, genetic algorithms, and their integration.
ANFIS Framework
Deep insights into Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and how they can model complex functions.
Hands-on MATLAB Exercises
Includes MATLAB code and simulation results for better visualization and practice.
Real-world Applications
Examples span across control systems, decision-making, pattern recognition, and industrial modeling.
Unified Soft Computing Approach
Explains how different AI methods can be hybridized to solve complex nonlinear problems.
Well-structured Learning Path
Includes summaries, solved examples, conceptual questions, and exercises after each chapter.
Interdisciplinary Utility
Useful for students and professionals in electrical engineering, computer science, robotics, and applied AI.
Authoritative Reference
Co-authored by Roger Jang, known for introducing the ANFIS model and widely respected in AI and soft computing.
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