Granular neural networks, pattern recognition and bioinformatics

This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration...

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Bibliographic Details
Main Authors: Pal, Sankar K., (Author), Ray, Shubhra S., (Author), Ganivada, Avatharam, (Author)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, 2017.
Series: Studies in computational intelligence ; v. 712.
Subjects:
Neural networks (Computer science)
Pattern recognition systems.
elektronické knihy
electronic books
ISBN: 9783319571157
9783319571133
Physical Description: 1 online resource (xix, 227 pages) : illustrations (some color)

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100 1 |a Pal, Sankar K.,  |e author. 
245 1 0 |a Granular neural networks, pattern recognition and bioinformatics /  |c Sankar K. Pal, Shubhra S. Ray, Avatharam Ganivada. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource (xix, 227 pages) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Studies in computational intelligence,  |x 1860-949X ;  |v volume 712 
504 |a Includes bibliographical references and index. 
505 0 |a Introduction to Granular Computing, Pattern Recognition and Data Mining -- Classification using Fuzzy Rough Granular Neural Networks -- Clustering using Fuzzy Rough Granular Self-Organizing Map -- Fuzzy Rough Granular Neural Network and Unsupervised Feature Selection. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules, . The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Neural networks (Computer science) 
650 0 |a Pattern recognition systems. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Ray, Shubhra S.,  |e author. 
700 1 |a Ganivada, Avatharam,  |e author. 
776 0 8 |i Printed edition:  |z 9783319571133 
830 0 |a Studies in computational intelligence ;  |v v. 712.  |x 1860-949X 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-57115-7  |y Plný text 
992 |c NTK-SpringerENG 
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993 |x NEPOSILAT  |y EIZ 

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