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Neural Network And Fuzzy Logic


Neural Network And Fuzzy Logic
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Neural Networks Fuzzy Logic And Genetic Algorithm


Neural Networks Fuzzy Logic And Genetic Algorithm
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Author : S. RAJASEKARAN
language : en
Publisher: PHI Learning Pvt. Ltd.
Release Date : 2003-01-01

Neural Networks Fuzzy Logic And Genetic Algorithm written by S. RAJASEKARAN and has been published by PHI Learning Pvt. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-01 with Computers categories.


This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems. The applications, demonstrative of the potential of the architectures, have been chosen from diverse disciplines of science and engineering. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year post-graduate engineering levels. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.



Neural Networks Fuzzy Logic


Neural Networks Fuzzy Logic
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Author : K. Vinoth Kumar
language : en
Publisher: Seagull Books Pvt Ltd
Release Date : 2009

Neural Networks Fuzzy Logic written by K. Vinoth Kumar and has been published by Seagull Books Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Fuzzy logic categories.




Understanding Neural Networks And Fuzzy Logic


Understanding Neural Networks And Fuzzy Logic
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Author : Stamatios V. Kartalopoulos
language : en
Publisher: Wiley-IEEE Press
Release Date : 1996

Understanding Neural Networks And Fuzzy Logic written by Stamatios V. Kartalopoulos and has been published by Wiley-IEEE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.


Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this carefully organized state-of-the-art textbook. Previously tested at a number of noteworthy conference tutorials, the simple numerical examples presented in this book provide excellent tools for progressive learning. UNDERSTANDING NEURAL NETWORKS AND FUZZY LOGIC offers a simple presentation and bottom-up approach that is ideal for working professional engineers, undergraduates, medical/biology majors, and anyone with a nonspecialist background. Sponsored by: IEEE Neural Networks Council



Foundations Of Neural Networks Fuzzy Systems And Knowledge Engineering


Foundations Of Neural Networks Fuzzy Systems And Knowledge Engineering
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Author : Nikola K. Kasabov
language : en
Publisher: Marcel Alencar
Release Date : 1996

Foundations Of Neural Networks Fuzzy Systems And Knowledge Engineering written by Nikola K. Kasabov and has been published by Marcel Alencar this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Artificial intelligence categories.


Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.



Neural Networks And Fuzzy Logic Control On Personal Computers And Workstations


Neural Networks And Fuzzy Logic Control On Personal Computers And Workstations
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Author : Granino Arthur Korn
language : en
Publisher: MIT Press (MA)
Release Date : 1995

Neural Networks And Fuzzy Logic Control On Personal Computers And Workstations written by Granino Arthur Korn and has been published by MIT Press (MA) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.


Neural Networks and Fuzzy-Logic Control introduces a simple integrated environment for programming displays and report generation. It includes the only currently available software that permits combined simulation of multiple neural networks, fuzzy-logic controllers, and dynamic systems such as robots or physiological models. The enclosed educational version of DESIRE/NEUNET differs for the full system mainly in the size of its data area and includes a compiler, two screen editors, color graphics, and many ready-to-run examples. The software lets users or instructors add their own help screens and interactive menus. The version of DESIRE/NEUNET included here is for PCs, viz. 286/287, 386/387, 486DX, Pentium, P6, SX with math coprocessor.



Neural Network And Fuzzy Logic


Neural Network And Fuzzy Logic
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Author : Surender K. Dass
language : en
Publisher:
Release Date : 2006-01-01

Neural Network And Fuzzy Logic written by Surender K. Dass and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Neural networks (Computer science) categories.




Neural Network And Fuzzy Logic Applications In C C


Neural Network And Fuzzy Logic Applications In C C
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Author : Stephen T. Welstead
language : en
Publisher:
Release Date : 2005

Neural Network And Fuzzy Logic Applications In C C written by Stephen T. Welstead and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.




Fuzzy Neural Network Theory And Application


Fuzzy Neural Network Theory And Application
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Author : Puyin Liu
language : en
Publisher: World Scientific
Release Date : 2004

Fuzzy Neural Network Theory And Application written by Puyin Liu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.


This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering. Contents: Fuzzy Neural Networks for Storing and Classifying; Fuzzy Associative Memory OCo Feedback Networks; Regular Fuzzy Neural Networks; Polygonal Fuzzy Neural Networks; Approximation Analysis of Fuzzy Systems; Stochastic Fuzzy Systems and Approximations; Application of FNN to Image Restoration. Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing."



Explainable Neural Networks Based On Fuzzy Logic And Multi Criteria Decision Tools


Explainable Neural Networks Based On Fuzzy Logic And Multi Criteria Decision Tools
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Author : József Dombi
language : en
Publisher: Springer Nature
Release Date : 2021-04-28

Explainable Neural Networks Based On Fuzzy Logic And Multi Criteria Decision Tools written by József Dombi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Technology & Engineering categories.


The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable – and even, in many cases, more efficient. Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.



Knowledge Based Neurocomputing A Fuzzy Logic Approach


Knowledge Based Neurocomputing A Fuzzy Logic Approach
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Author : Eyal Kolman
language : en
Publisher: Springer
Release Date : 2008-10-18

Knowledge Based Neurocomputing A Fuzzy Logic Approach written by Eyal Kolman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-18 with Computers categories.


In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.