Fuzzy Mathematical Approach to Pattern Recognition

Fuzzy Mathematical Approach to Pattern Recognition PDF Author: Sankar K. Pal
Publisher:
ISBN: 9780852261934
Category : Apprentissage automatique
Languages : en
Pages : 280

Get Book Here

Book Description

Fuzzy Mathematical Approach to Pattern Recognition

Fuzzy Mathematical Approach to Pattern Recognition PDF Author: Sankar K. Pal
Publisher:
ISBN: 9780852261934
Category : Apprentissage automatique
Languages : en
Pages : 280

Get Book Here

Book Description


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

Get Book Here

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.

Introduction to Pattern Recognition

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

Get Book Here

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.

Fuzzy Techniques in Pattern Recognition

Fuzzy Techniques in Pattern Recognition PDF Author: Abraham Kandel
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 376

Get Book Here

Book Description


Fuzzy Sets and Their Applications to Cognitive and Decision Processes

Fuzzy Sets and Their Applications to Cognitive and Decision Processes PDF Author: Lotfi A. Zadeh
Publisher: Academic Press
ISBN: 1483265919
Category : Mathematics
Languages : en
Pages : 507

Get Book Here

Book Description
Fuzzy Sets and Their Applications to Cognitive and Decision Processes contains the proceedings of the U.S.-Japan Seminar on Fuzzy Sets and Their Applications, held at the University of California in Berkeley, California, on July 1-4, 1974. The seminar provided a forum for discussing a broad spectrum of topics related to the theory of fuzzy sets, ranging from its mathematical aspects to applications in human cognition, communication, decision making, and engineering systems analysis. Comprised of 19 chapters, this book begins with an introduction to the calculus of fuzzy restrictions, followed by a discussion on fuzzy programs and their execution. Subsequent chapters focus on fuzzy relations, fuzzy graphs, and their applications to clustering analysis; risk and decision making in a fuzzy environment; fractionally fuzzy grammars and their application to pattern recognition; and applications of fuzzy sets in psychology. An approach to pattern recognition and associative memories using fuzzy logic is also described. This monograph will be of interest to students and practitioners in the fields of computer science, engineering, psychology, and applied mathematics.

Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms PDF Author: James C. Bezdek
Publisher: Springer Science & Business Media
ISBN: 147570450X
Category : Mathematics
Languages : en
Pages : 267

Get Book Here

Book Description
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.

Soft Computing Approach to Pattern Recognition and Image Processing

Soft Computing Approach to Pattern Recognition and Image Processing PDF Author: Ashish Ghosh
Publisher: World Scientific
ISBN: 9789812776235
Category : Computers
Languages : en
Pages : 374

Get Book Here

Book Description
This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications. The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research. The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike. Contents: Pattern Recognition: Multiple Classifier Systems; Building Decision Trees from the Fourier Spectrum of a Tree Ensemble; Clustering Large Data Sets; Multi-objective Variable String Genetic Classifier: Application to Remote Sensing Imagery; Image Processing and Vision: Dissimilarity Measures Between Fuzzy Sets or Fuzzy Structures; Early Vision: Concepts and Algorithms; Self-organizing Neural Network for Multi-level Image Segmentation; Geometric Transformation by Moment Method with Wavelet Matrix; New Computationally Efficient Algorithms for Video Coding; Soft Computing for Computational Media Aesthetics: Analyzing Video Content for Meaning; Granular Computing and Case Based Reasoning: Towards Granular Multi-agent Systems; Granular Computing and Pattern Recognition; Case Base Maintenance: A Soft Computing Perspective; Real Life Applications: Autoassociative Neural Network Models for Pattern Recognition Tasks in Speech and Image; Protein Structure Prediction Using Soft Computing; Pattern Classification for Biological Data Mining. Readership: Upper level undergraduates, graduates, researchers, academics and industrialists.

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.

Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering

Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering PDF Author: Larisa Angstenberger
Publisher: Springer Science & Business Media
ISBN: 940171312X
Category : Mathematics
Languages : en
Pages : 303

Get Book Here

Book Description
Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification.

Introduction To Pattern Recognition: Statistical, Structural, Neural And Fuzzy Logic Approaches

Introduction To Pattern Recognition: Statistical, Structural, Neural And Fuzzy Logic Approaches PDF Author: Menahem Friedman
Publisher: World Scientific Publishing Company
ISBN: 9813105186
Category : Computers
Languages : en
Pages : 343

Get Book Here

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.