Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

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Publisher : Springer Science & Business Media
ISBN 13 : 0387245790
Total Pages : 786 pages
Book Rating : 4.99/5 ( download)

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Book Synopsis Fuzzy Models and Algorithms for Pattern Recognition and Image Processing by : James C. Bezdek

Download or read book Fuzzy Models and Algorithms for Pattern Recognition and Image Processing written by James C. Bezdek and published by Springer Science & Business Media. This book was released on 2006-09-28 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Unique to this volume in the Kluwer Handbooks of Fuzzy Sets Series is the fact that this book was written in its entirety by its four authors. A single notation, presentation style, and purpose are used throughout. The result is an extensive unified treatment of many fuzzy models for pattern recognition. The main topics are clustering and classifier design, with extensive material on feature analysis relational clustering, image processing and computer vision. Also included are numerous figures, images and numerical examples that illustrate the use of various models involving applications in medicine, character and word recognition, remote sensing, military image analysis, and industrial engineering.

Fuzzy Models for Pattern Recognition

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Publisher : Institute of Electrical & Electronics Engineers(IEEE)
ISBN 13 :
Total Pages : 560 pages
Book Rating : 4.07/5 ( download)

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Book Synopsis Fuzzy Models for Pattern Recognition by : James C. Bezdek

Download or read book Fuzzy Models for Pattern Recognition written by James C. Bezdek and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1992 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Pattern Recognition with Fuzzy Objective Function Algorithms

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Publisher : Springer Science & Business Media
ISBN 13 : 147570450X
Total Pages : 267 pages
Book Rating : 4.01/5 ( download)

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Book Synopsis Pattern Recognition with Fuzzy Objective Function Algorithms by : James C. Bezdek

Download or read book Pattern Recognition with Fuzzy Objective Function Algorithms written by James C. Bezdek and published by Springer Science & Business Media. This book was released on 2013-03-13 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

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Publisher : Springer
ISBN 13 : 9780387505206
Total Pages : 0 pages
Book Rating : 4.02/5 ( download)

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Book Synopsis Fuzzy Models and Algorithms for Pattern Recognition and Image Processing by : James C. Bezdek

Download or read book Fuzzy Models and Algorithms for Pattern Recognition and Image Processing written by James C. Bezdek and published by Springer. This book was released on 2008-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Unique to this volume in the Kluwer Handbooks of Fuzzy Sets Series is the fact that this book was written in its entirety by its four authors. A single notation, presentation style, and purpose are used throughout. The result is an extensive unified treatment of many fuzzy models for pattern recognition. The main topics are clustering and classifier design, with extensive material on feature analysis relational clustering, image processing and computer vision. Also included are numerous figures, images and numerical examples that illustrate the use of various models involving applications in medicine, character and word recognition, remote sensing, military image analysis, and industrial engineering.

Rough-Fuzzy Pattern Recognition

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Publisher : John Wiley & Sons
ISBN 13 : 111800440X
Total Pages : 312 pages
Book Rating : 4.01/5 ( download)

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Book Synopsis Rough-Fuzzy Pattern Recognition by : Pradipta Maji

Download or read book Rough-Fuzzy Pattern Recognition written by Pradipta Maji and published by John Wiley & Sons. This book was released on 2012-02-14 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection. Rough-Fuzzy Pattern Recognition examines the important underlying theory as well as algorithms and applications, helping readers see the connections between theory and practice. The first chapter provides an introduction to pattern recognition and data mining, including the key challenges of working with high-dimensional, real-life data sets. Next, the authors explore such topics and issues as: Soft computing in pattern recognition and data mining A mathematical framework for generalized rough sets, incorporating the concept of fuzziness in defining the granules as well as the set Selection of non-redundant and relevant features of real-valued data sets Selection of the minimum set of basis strings with maximum information for amino acid sequence analysis Segmentation of brain MR images for visualization of human tissues Numerous examples and case studies help readers better understand how pattern recognition models are developed and used in practice. This text—covering the latest findings as well as directions for future research—is recommended for both students and practitioners working in systems design, pattern recognition, image analysis, data mining, bioinformatics, soft computing, and computational intelligence.

Computational Intelligence for Pattern Recognition

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Publisher : Springer
ISBN 13 : 3319896296
Total Pages : 428 pages
Book Rating : 4.98/5 ( download)

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Book Synopsis Computational Intelligence for Pattern Recognition by : Witold Pedrycz

Download or read book Computational Intelligence for Pattern Recognition written by Witold Pedrycz and published by Springer. This book was released on 2018-04-30 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Model Identification

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Publisher : Springer Science & Business Media
ISBN 13 : 3642607675
Total Pages : 334 pages
Book Rating : 4.77/5 ( download)

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Book Synopsis Fuzzy Model Identification by : Hans Hellendoorn

Download or read book Fuzzy Model Identification written by Hans Hellendoorn and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past few years two principally different approaches to the design of fuzzy controllers have emerged: heuristics-based design and model-based design. The main motivation for the heuristics-based design is given by the fact that many industrial processes are still controlled in one of the following two ways: - The process is controlled manually by an experienced operator. - The process is controlled by an automatic control system which needs manual, on-line 'trimming' of its parameters by an experienced operator. In both cases it is enough to translate in terms of a set of fuzzy if-then rules the operator's manual control algorithm or manual on-line 'trimming' strategy in order to obtain an equally good, or even better, wholly automatic fuzzy control system. This implies that the design of a fuzzy controller can only be done after a manual control algorithm or trimming strategy exists. It is admitted in the literature on fuzzy control that the heuristics-based approach to the design of fuzzy controllers is very difficult to apply to multiple-inputjmultiple-output control problems which represent the largest part of challenging industrial process control applications. Furthermore, the heuristics-based design lacks systematic and formally verifiable tuning tech niques. Also, studies of the stability, performance, and robustness of a closed loop system incorporating a heuristics-based fuzzy controller can only be done via extensive simulations.

Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition

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Publisher : World Scientific
ISBN 13 : 9814498858
Total Pages : 239 pages
Book Rating : 4.52/5 ( download)

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Book Synopsis Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition by : Zheru Chi

Download or read book Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition written by Zheru Chi and published by World Scientific. This book was released on 1996-10-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Introduction:Basic Concepts of Fuzzy SetsFuzzy RelationsFuzzy Models for Image Processing and Pattern RecognitionMembership Functions:IntroductionHeuristic SelectionsClustering ApproachesTuning of Membership FunctionsConcluding RemarksOptimal Image Thresholding:IntroductionThreshold Selection Based on Statistical Decision TheoryNon-fuzzy Thresholding AlgorithmsFuzzy Thresholding AlgorithmUnified Formulation of Three Thresholding AlgorithmsMultilevel ThresholdingApplicationsConcluding RemarksFuzzy Clustering:IntroductionC-Means AlgorithmFuzzy C-Means AlgorithmComparison between Hard and Fuzzy Clustering AlgorithmsCluster ValidityApplicationsConcluding RemarksLine Pattern Matching:IntroductionSimilarity Measures between Line SegmentsBasic Matching AlgorithmDealing with Noisy PatternsDealing with Rotated PatternsApplicationsConcluding RemarksFuzzy Rule-based Systems:IntroductionLearning from ExamplesDecision Tree ApproachFuzzy Aggregation Network ApproachMinimization of Fuzzy RulesDefuzzification and OptimizationApplicationsConcluding RemarksCombined Classifiers:IntroductionVoting SchemesMaximum Posteriori ProbabilityMultilayer Perceptron ApproachFuzzy Measures and Fuzzy IntegralsApplicationsConcluding Remarks Readership: Engineers and computer scientists. keywords:

Fuzzy Modeling and Control

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Publisher : Physica
ISBN 13 : 3790818240
Total Pages : 737 pages
Book Rating : 4.46/5 ( download)

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Book Synopsis Fuzzy Modeling and Control by : Andrzej Piegat

Download or read book Fuzzy Modeling and Control written by Andrzej Piegat and published by Physica. This book was released on 2013-03-19 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The attraction of fuzzy modeling results from its intelligibility and the high effectiveness of the models obtained. Owing to this the modeling can be applied for the solution of problems which could not be solved till now with any known conventional methods. The book provides the reader with an advanced introduction to the problems of fuzzy modeling and to one of its most important applications: fuzzy control. It is based on the latest and most significant knowledge of the subject and can be used not only by control specialists but also by specialists working in any field requiring plant modeling, process modeling, and systems modeling, e.g. economics, business, medicine, agriculture,and meteorology.

Computer Models of Speech Using Fuzzy Algorithms

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Publisher : Springer Science & Business Media
ISBN 13 : 1461337429
Total Pages : 505 pages
Book Rating : 4.23/5 ( download)

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Book Synopsis Computer Models of Speech Using Fuzzy Algorithms by : Renato de Mori

Download or read book Computer Models of Speech Using Fuzzy Algorithms written by Renato de Mori and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is with great pleasure that I present this third volume of the series "Advanced Applications in Pattern Recognition." It represents the summary of many man- (and woman-) years of effort in the field of speech recognition by tne author's former team at the University of Turin. It combines the best results in fuzzy-set theory and artificial intelligence to point the way to definitive solutions to the speech-recognition problem. It is my hope that it will become a classic work in this field. I take this opportunity to extend my thanks and appreciation to Sy Marchand, Plenum's Senior Editor responsible for overseeing this series, and to Susan Lee and Jo Winton, who had the monumental task of preparing the camera-ready master sheets for publication. Morton Nadler General Editor vii PREFACE Si parva licet componere magnis Virgil, Georgics, 4,176 (37-30 B.C.) The work reported in this book results from years of research oriented toward the goal of making an experimental model capable of understanding spoken sentences of a natural language. This is, of course, a modest attempt compared to the complexity of the functions performed by the human brain. A method is introduced for conce1v1ng modules performing perceptual tasks and for combining them in a speech understanding system.