Neuro-Fuzzy Pattern Recognition

Neuro-Fuzzy Pattern Recognition PDF Author: Sankar K. Pal
Publisher: Wiley-Interscience
ISBN:
Category : Computers
Languages : en
Pages : 418

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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.

Neuro-Fuzzy Pattern Recognition

Neuro-Fuzzy Pattern Recognition PDF Author: Sankar K. Pal
Publisher: Wiley-Interscience
ISBN:
Category : Computers
Languages : en
Pages : 418

Get Book Here

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.

Neuro-fuzzy Pattern Recognition

Neuro-fuzzy Pattern Recognition PDF Author: Horst Bunke
Publisher: World Scientific
ISBN: 9810244185
Category : Computers
Languages : en
Pages : 276

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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.

Computational Intelligence for Pattern Recognition

Computational Intelligence for Pattern Recognition PDF Author: Witold Pedrycz
Publisher: Springer
ISBN: 3319896296
Category : Technology & Engineering
Languages : en
Pages : 431

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Book Description
The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.

Fuzzy and Neuro-Fuzzy Intelligent Systems

Fuzzy and Neuro-Fuzzy Intelligent Systems PDF Author: Ernest Czogala
Publisher: Physica
ISBN: 3790818534
Category : Computers
Languages : en
Pages : 207

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Book Description
Intelligence systems. We perfonn routine tasks on a daily basis, as for example: • recognition of faces of persons (also faces not seen for many years), • identification of dangerous situations during car driving, • deciding to buy or sell stock, • reading hand-written symbols, • discriminating between vines made from Sauvignon Blanc, Syrah or Merlot grapes, and others. Human experts carry out the following: • diagnosing diseases, • localizing faults in electronic circuits, • optimal moves in chess games. It is possible to design artificial systems to replace or "duplicate" the human expert. There are many possible definitions of intelligence systems. One of them is that: an intelligence system is a system able to make decisions that would be regarded as intelligent ifthey were observed in humans. Intelligence systems adapt themselves using some example situations (inputs of a system) and their correct decisions (system's output). The system after this learning phase can make decisions automatically for future situations. This system can also perfonn tasks difficult or impossible to do for humans, as for example: compression of signals and digital channel equalization.

Introduction to Pattern Recognition

Introduction to Pattern Recognition PDF Author: Menahem Friedman
Publisher: World Scientific
ISBN: 9789810233129
Category : Computers
Languages : en
Pages : 350

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Book Description
This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM

NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM PDF Author: S. RAJASEKARAN
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120321863
Category : Computers
Languages : en
Pages : 459

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Book Description
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.

Compensatory Genetic Fuzzy Neural Networks and Their Applications

Compensatory Genetic Fuzzy Neural Networks and Their Applications PDF Author: Yan-Qing Zhang
Publisher: World Scientific
ISBN: 9789810233495
Category : Computers
Languages : en
Pages : 206

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Book Description
This book presents a powerful hybrid intelligent system based on fuzzy logic, neural networks, genetic algorithms and related intelligent techniques. The new compensatory genetic fuzzy neural networks have been widely used in fuzzy control, nonlinear system modeling, compression of a fuzzy rule base, expansion of a sparse fuzzy rule base, fuzzy knowledge discovery, time series prediction, fuzzy games and pattern recognition. This effective soft computing system is able to perform both linguistic-word-level fuzzy reasoning and numerical-data-level information processing. The book also proposes various novel soft computing techniques.

Hybrid Methods in Pattern Recognition

Hybrid Methods in Pattern Recognition PDF Author: Horst Bunke
Publisher: World Scientific
ISBN: 9810248326
Category : Technology & Engineering
Languages : en
Pages : 338

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Book Description
The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and so on. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.

Fuzzy Mathematical Approach to Pattern Recognition

Fuzzy Mathematical Approach to Pattern Recognition PDF Author: Sankar K. Pal
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 304

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Book Description
This book aims to present results of investigations, both experimental and theoretical, into the effectiveness of fuzzy algorithms as classification tools in some problems concerned with the field of pattern recognition and image processing. Compares results to those obtained with statistical classification techniques.

Statistical Pattern Recognition

Statistical Pattern Recognition PDF Author: Andrew R. Webb
Publisher: John Wiley & Sons
ISBN: 0470854782
Category : Mathematics
Languages : en
Pages : 516

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Book Description
Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a