Kindly note that we have put a lot of effort into researching the best books on Neural Nets, Fuzzy Systems and Applications subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Neural Nets, Fuzzy Systems and Applications" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
|1. “Neural Networks: A comprehensive foundation” by Haykin S
Book Review: This book discusses neural networks from an engineering perspective. The book includes the learning process, back propagation, radial basis functions, recurrent networks, modular networks, neurodynamics and VLSI implementation. The book also provides detailed analysis of backpropagation learning and multi-layer perceptrons. The book contains chapters along with chapter objectives, problems, worked examples, illustrations and glossary. The book also covers various facets of neural networks along with the potential applications.
|2. “Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence” by Kosko B
“Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence” Book Review: The book is basically for students graduating in engineering, computer science, mathematics, psychology and biology. It features trainable dynamical systems, mechanisms and principles of adaptation, self-organization, convergence and global stability, new geometric theory of fuzzy sets, systems and associative memories. The book combines the field of neutral network and fuzzy systems at theoretical level. It also highlights applications of new adaptive fuzzy systems in control and signal processing.
|3. “Digital Neural Networks” by Kung S Y
“Digital Neural Networks” Book Review: This book will be excellent for electrical engineers, computer engineers and computer scientists. The book contains descriptions of various neural models. It provides knowledge about both fundamental theory and practical implementation of various neural models. For better understanding of the readers, applications, algorithms and architecture of neural networks are described clearly in this book.
|4. “Fuzzy Sets and Fuzzy Logic” by Klir G J and Yuan B
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Book Review: The book demonstrates the recent advancements made in the field of fuzzy sets and fuzzy logic. The book also illustrates a variety of applications of fuzzy sets and fuzzy logic. The book contains basic types of fuzzy sets, connection between fuzzy and crisp sets, fuzzy numbers and arithmetic operations on them, fuzzy relations and equations. The book also deals with the applications of fuzzy set theory and fuzzy logic, fuzzy systems and controllers, fuzzy databases, fuzzy decision making and many engineering applications. This book is useful for people interested in fuzzy set theory and fuzzy logic.
|5. “Neuro-Fuzzy and Soft Computing” by Jang J S R
Book Review: This book stresses on the theoretical concepts of fuzzy and soft computing and also focuses on empirical observations and verification of various applications. The book contains numerous exercises which are programmed using MATLAB along with practical problem solving. This is a self-study book for many researchers who are interested in learning basic and advanced neuro fuzzy and soft computing within the framework of computational intelligence.
| 6. “Fuzzy Logic and Soft Computing” by BOUCHON-MEUNIER BERNADETTE
“Fuzzy Logic and Soft Computing” Book Review: The book is basically about problems and their solutions in ‘intelligent systems’. The problems that occur when information is imprecise, uncertain, incomplete, or of different linguistic nature are mentioned in the book. Various methods like probabilistic, fuzzy, logical, evidential and network-based frameworks for solving these problems are explained. The book consists of the topics such as fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, bayesian networks and other network methods, as well as logic-based systems.
|7. “Supervisory Control of Concurrent Systems: A Petri Net Structural Approach” by Panos J Antsaklis|
|8. “Petri Nets and Other Models of Concurrency” by P S Thiagarajan and Susanna Donatelli|
| 9. “Timed Petri Nets: Theory and Application” by Wang Jiacun
“Timed Petri Nets: Theory and Application” Book Review: The book contains systematic and comprehensive theory of timed Petri nets. It also consists of many industrial applications of the preceding topic, so that the readers can apply bookish knowledge easily in their respective fields. The book also contains many developments and latest research in timed Petri nets. The book will be very helpful for the researchers and practitioners in the area of Discrete Event Dynamic Systems.
| 10. “Artificial Neural Nets and Genetic Algorithms” by Rudolf F Albrecht
“Artificial Neural Nets and Genetic Algorithms” Book Review: The book is based on artificial neural networks and genetic algorithms, which have their origin in mathematical models. These areas act as a base in understanding natural processes. This book is intended to focus on the process model rather than the process. It features new significant computational techniques, which have application in a large number of diverse fields. Topics of this book are related to previously mentioned techniques and applications. The book will help readers to apply genetic algorithms and theorems to real problems.
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