Pattern Recognition In Soft Computing Paradigm

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Pattern Recognition in Soft Computing Paradigm

Pattern Recognition in Soft Computing Paradigm
Author :
Publisher : World Scientific
Total Pages : 411
Release :
ISBN-10 : 9789812811691
ISBN-13 : 9812811699
Rating : 4/5 (699 Downloads)

Book Synopsis Pattern Recognition in Soft Computing Paradigm by : Nikhil R. Pal

Download or read book Pattern Recognition in Soft Computing Paradigm written by Nikhil R. Pal and published by World Scientific. This book was released on 2001 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition (PR) consists of three important tasks: feature analysis, clustering and classification. Image analysis can also be viewed as a PR task. Feature analysis is a very important step in designing any useful PR system because its effectiveness depends heavily on the set of features used to realise the system. A distinguishing feature of this volume is that it deals with all three aspects of PR, namely feature analysis, clustering and classifier design. It also encompasses image processing methodologies and image retrieval with subjective information. The other interesting aspect of the volume is that it covers all three major facets of soft computing: fuzzy logic, neural networks and evolutionary computing. Contents: Dimensionality Reduction Techniques for Interactive Visualization, Exploratory Data Analysis, and Classification (A KAnig); Feature Selection by Artificial Neural Network for Pattern Classification (B Chakraborty); A New Clustering with Estimation of Cluster Number Based on Genetic Algorithm (K Imai et al.); Minimizing the Measurement Cost in the Classification of New Samples by Neural-Network-Based Classifiers (H Ishibuchi & M Nii); Extraction of Fuzzy Rules from Numerical Data for Classifiers (N R Pal & A Sarkar); A Texture Image Segmentation Method Using Neural Networks and Binary Features (J Zhang & S Oe); Image Retrieval System Based on Subjective Information (K Yoshida et al.); and other papers. Readership: Graduate students, researchers and lecturers in pattern recognition and image analysis."


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