Neural Network and Fuzzy Logic Applications in C-C++
Author : Stephen T Welstead
Publisher :
Page : pages
File Size : 34,85 MB
Release : 1994-08-01
Category :
ISBN : 9785554800092
Neural Network and Fuzzy Logic Applications in C/C++
Author : Stephen T. Welstead
Publisher : Wiley
Page : 494 pages
File Size : 24,22 MB
Release : 1994-07-13
Category : Computers
ISBN : 9780471309741
Book Description
Using an engineering and science perspective, it explores diverse neural network, fuzzy logic and genetic algorithm techniques plus developing applications best suited for each of the methods discussed. Sample results are described and judgment made as to how well each application worked. The book/disk set includes an object-oriented user interface along with the code for numerous programs.
Neural Network and Fuzzy Logic Applications in C
Author : Stephen T. Welstead
Publisher :
Page : pages
File Size : 41,18 MB
Release : 1994
Category :
ISBN :
Book Description
Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms
Author : Lakhmi C. Jain
Publisher : CRC Press
Page : 366 pages
File Size : 40,76 MB
Release : 2020-01-29
Category : Computers
ISBN : 1000722945
Book Description
Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.
An Introduction to Fuzzy Logic Applications in Intelligent Systems
Author : Ronald R. Yager
Publisher : Springer Science & Business Media
Page : 358 pages
File Size : 15,77 MB
Release : 2012-12-06
Category : Computers
ISBN : 1461536405
Book Description
An Introduction to Fuzzy Logic Applications in Intelligent Systems consists of a collection of chapters written by leading experts in the field of fuzzy sets. Each chapter addresses an area where fuzzy sets have been applied to situations broadly related to intelligent systems. The volume provides an introduction to and an overview of recent applications of fuzzy sets to various areas of intelligent systems. Its purpose is to provide information and easy access for people new to the field. The book also serves as an excellent reference for researchers in the field and those working in the specifics of systems development. People in computer science, especially those in artificial intelligence, knowledge-based systems, and intelligent systems will find this to be a valuable sourcebook. Engineers, particularly control engineers, will also have a strong interest in this book. Finally, the book will be of interest to researchers working in decision support systems, operations research, decision theory, management science and applied mathematics. An Introduction to Fuzzy Logic Applications in Intelligent Systems may also be used as an introductory text and, as such, it is tutorial in nature.
C++ Neural Networks and Fuzzy Logic
Author : Hayagriva V. Rao
Publisher :
Page : 551 pages
File Size : 31,91 MB
Release : 1996
Category : C++ (Computer program language)
ISBN : 9788170296942
Book Description
Neuro-fuzzy Pattern Recognition
Author : Horst Bunke
Publisher : World Scientific
Page : 276 pages
File Size : 35,48 MB
Release : 2000-12-22
Category : Computers
ISBN : 9814492396
Book Description
Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition. Neuro-fuzzy systems aim at combining the advantages of the two paradigms. This book is a collection of papers describing state-of-the-art work in this emerging field. It covers topics such as feature selection, classification, classifier training, and clustering. Also included are applications of neuro-fuzzy systems in speech recognition, land mine detection, medical image analysis, and autonomous vehicle control. The intended audience includes graduate students in computer science and related fields, as well as researchers at academic institutions and in industry.
Neuro-Fuzzy Pattern Recognition
Author : Sankar K. Pal
Publisher : Wiley-Interscience
Page : 418 pages
File Size : 10,37 MB
Release : 1999
Category : Computers
ISBN :
Book Description
The neuro-fuzzy approach to pattern recognition-a unique overview Recent years have seen a surge of interest in neuro-fuzzy computing, which combines fuzzy logic, neural networks, and soft computing techniques. This book focuses on the application of this new tool to the rapidly evolving area of pattern recognition. Written by two leaders in neural networks and soft computing research, this landmark work presents a unified, comprehensive treatment of the state of the art in the field. The authors consolidate a wealth of information previously cattered in disparate articles, journals, and edited volumes, explaining both the theory of neuro-fuzzy computing and the latest methodologies for performing different pattern recognition tasks in the neuro-fuzzy network-classification, feature evaluation, rule generation, knowledge extraction, and hybridization. Special emphasis is given to the integration of neuro-fuzzy methods with rough sets and genetic algorithms (GAs) to ensure more efficient recognition systems. Clear, concise, and fully referenced, Neuro-Fuzzy Pattern Recognition features extensive examples and highlights key applications in speech, machine learning, medicine, and forensic science. It is an extremely useful resource for scientists and engineers in laboratories and industry as well as for anyone seeking up-to-date information on the advantages of neuro-fuzzy pattern recognition in new computer technologies.
Fuzzy Neural Network Theory and Application
Author : Puyin Liu
Publisher : World Scientific
Page : 400 pages
File Size : 18,71 MB
Release : 2004
Category : Computers
ISBN : 9789812794215
Book Description
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."
Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition
Author : Patricia Melin
Publisher : Springer Science & Business Media
Page : 216 pages
File Size : 36,51 MB
Release : 2011-10-18
Category : Computers
ISBN : 3642241387
Book Description
This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
