Rough-Neural Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 3642188591
Total Pages : 741 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Rough-Neural Computing by : Sankar Kumar Pal

Download or read book Rough-Neural Computing written by Sankar Kumar Pal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g. in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, genetic algorithms, and others. It is well understood now in the soft computing community that hybrid approaches combining various paradigms are very promising approaches for solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neuro computing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

Rough-Neural Computing

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Publisher :
ISBN 13 : 9783642188602
Total Pages : 764 pages
Book Rating : 4.1/5 (886 download)

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Book Synopsis Rough-Neural Computing by : Sankar Kumar Pal

Download or read book Rough-Neural Computing written by Sankar Kumar Pal and published by . This book was released on 2003-09-22 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Neural Computation

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Author :
Publisher : Academic Press
ISBN 13 : 0128113197
Total Pages : 660 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Neural Computation by : Pijush Samui

Download or read book Handbook of Neural Computation written by Pijush Samui and published by Academic Press. This book was released on 2017-07-18 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Granular Neural Networks, Pattern Recognition and Bioinformatics

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Author :
Publisher : Springer
ISBN 13 : 331957115X
Total Pages : 241 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Granular Neural Networks, Pattern Recognition and Bioinformatics by : Sankar K. Pal

Download or read book Granular Neural Networks, Pattern Recognition and Bioinformatics written by Sankar K. Pal and published by Springer. This book was released on 2017-05-02 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Pattern Recognition And Big Data

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Publisher : World Scientific
ISBN 13 : 9813144564
Total Pages : 875 pages
Book Rating : 4.8/5 (131 download)

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Book Synopsis Pattern Recognition And Big Data by : Sankar Kumar Pal

Download or read book Pattern Recognition And Big Data written by Sankar Kumar Pal and published by World Scientific. This book was released on 2016-12-15 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.

Soft Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 3662043351
Total Pages : 335 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Soft Computing by : Andrea Tettamanzi

Download or read book Soft Computing written by Andrea Tettamanzi and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

Soft Computing in Acoustics

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Publisher : Physica
ISBN 13 : 3790818755
Total Pages : 254 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Soft Computing in Acoustics by : Bozena Kostek

Download or read book Soft Computing in Acoustics written by Bozena Kostek and published by Physica. This book was released on 2013-06-29 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of some selected soft computing methods to acoustics and sound engineering are presented in this book. The aim of this research study is the implementation of soft computing methods to musical signal analysis and to the recognition of musical sounds and phrases. Accordingly, some methods based on such learning algorithms as neural networks, rough sets and fuzzy-logic were conceived, implemented and tested. Additionally, the above-mentioned methods were applied to the analysis and verification of subjective testing results. The last problem discussed within the framework of this book was the problem of fuzzy control of the classical pipe organ instrument. The obtained results show that computational intelligence and soft computing may be used for solving some vital problems in both musical and architectural acoustics.

Advances in Neural Networks - ISNN 2005

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Publisher : Springer Science & Business Media
ISBN 13 : 3540259139
Total Pages : 994 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Advances in Neural Networks - ISNN 2005 by : Xiaofeng Liao

Download or read book Advances in Neural Networks - ISNN 2005 written by Xiaofeng Liao and published by Springer Science & Business Media. This book was released on 2005-05-17 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005. The 483 revised papers presented were carefully reviewed and selected from 1.425 submissions. The papers are organized in topical sections on theoretical analysis, model design, learning methods, optimization methods, kernel methods, component analysis, pattern analysis, systems modeling, signal processing, image processing, financial analysis, control systems, robotic systems, telecommunication networks, incidence detection, fault diagnosis, power systems, biomedical applications, industrial applications, and other applications.

Neuro-Fuzzy Pattern Recognition

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Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 418 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Neuro-Fuzzy Pattern Recognition by : Sankar K. Pal

Download or read book Neuro-Fuzzy Pattern Recognition written by Sankar K. Pal and published by Wiley-Interscience. This book was released on 1999 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Neural Networks in Finance

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Publisher : Academic Press
ISBN 13 : 0124859674
Total Pages : 262 pages
Book Rating : 4.1/5 (248 download)

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Book Synopsis Neural Networks in Finance by : Paul D. McNelis

Download or read book Neural Networks in Finance written by Paul D. McNelis and published by Academic Press. This book was released on 2005-01-05 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

Neural Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 3642577601
Total Pages : 340 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Neural Networks by : Berndt Müller

Download or read book Neural Networks written by Berndt Müller and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.

Advances in Neural Networks - ISNN 2007

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Publisher : Springer Science & Business Media
ISBN 13 : 3540723927
Total Pages : 1345 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Advances in Neural Networks - ISNN 2007 by : Derong Liu

Download or read book Advances in Neural Networks - ISNN 2007 written by Derong Liu and published by Springer Science & Business Media. This book was released on 2007-05-24 with total page 1345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation The three volume set LNCS 4491/4492/4493 constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. The 262 revised long papers and 192 revised short papers presented were carefully reviewed and selected from a total of 1.975 submissions. The papers are organized in topical sections on neural fuzzy control, neural networks for control applications, adaptive dynamic programming and reinforcement learning, neural networks for nonlinear systems modeling, robotics, stability analysis of neural networks, learning and approximation, data mining and feature extraction, chaos and synchronization, neural fuzzy systems, training and learning algorithms for neural networks, neural network structures, neural networks for pattern recognition, SOMs, ICA/PCA, biomedical applications, feedforward neural networks, recurrent neural networks, neural networks for optimization, support vector machines, fault diagnosis/detection, communications and signal processing, image/video processing, and applications of neural networks.

Rough Sets and Current Trends in Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 354044274X
Total Pages : 654 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Rough Sets and Current Trends in Computing by : James J. Alpigini

Download or read book Rough Sets and Current Trends in Computing written by James J. Alpigini and published by Springer Science & Business Media. This book was released on 2002-09-25 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002, held in Malvern, PA, USA in October 2002. The 76 revised regular papers and short communications presented together with 2 keynotes and 5 plenary papers were carefully reviewed and selected from more than 100 submissions. The book offers topical sections on foundation and methods; granular and neural computing; probabilistic reasoning; data mining, machine learning and pattern recognition; Web mining; and applications.

Emerging Trends in Neuro Engineering and Neural Computation

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Publisher : Springer
ISBN 13 : 9811039577
Total Pages : 267 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Emerging Trends in Neuro Engineering and Neural Computation by : Asim Bhatti

Download or read book Emerging Trends in Neuro Engineering and Neural Computation written by Asim Bhatti and published by Springer. This book was released on 2017-03-23 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on neuro-engineering and neural computing, a multi-disciplinary field of research attracting considerable attention from engineers, neuroscientists, microbiologists and material scientists. It explores a range of topics concerning the design and development of innovative neural and brain interfacing technologies, as well as novel information acquisition and processing algorithms to make sense of the acquired data. The book also highlights emerging trends and advances regarding the applications of neuro-engineering in real-world scenarios, such as neural prostheses, diagnosis of neural degenerative diseases, deep brain stimulation, biosensors, real neural network-inspired artificial neural networks (ANNs) and the predictive modeling of information flows in neuronal networks. The book is broadly divided into three main sections including: current trends in technological developments, neural computation techniques to make sense of the neural behavioral data, and application of these technologies/techniques in the medical domain in the treatment of neural disorders.

Building Neural Networks

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Publisher : Addison-Wesley Professional
ISBN 13 : 9780201539219
Total Pages : 308 pages
Book Rating : 4.5/5 (392 download)

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Book Synopsis Building Neural Networks by : David M. Skapura

Download or read book Building Neural Networks written by David M. Skapura and published by Addison-Wesley Professional. This book was released on 1996 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organized by application areas, rather than by specific network architectures or learning algorithms, Building Neural Networks shows why certain networks are more suitable than others for solving specific kinds of problems. Skapura also reviews principles of neural information processing and furnishes an operations summary of the most popular neural-network processing models.

Handbook of Granular Computing

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Publisher : John Wiley & Sons
ISBN 13 : 0470724153
Total Pages : 1148 pages
Book Rating : 4.4/5 (77 download)

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Book Synopsis Handbook of Granular Computing by : Witold Pedrycz

Download or read book Handbook of Granular Computing written by Witold Pedrycz and published by John Wiley & Sons. This book was released on 2008-07-31 with total page 1148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of effectiveness, robustness and uncertainty. The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with contributions from leading experts in the field. Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set theory; hybrid methods and models of granular computing; and applications and case studies. Divided into 5 sections: Preliminaries, Fundamentals, Methodology and Algorithms, Development of Hybrid Models and Applications and Case Studies. Presents the flow of ideas in a systematic, well-organized manner, starting with the concepts and motivation and proceeding to detailed design that materializes in specific algorithms, applications and case studies. Provides the reader with a self-contained reference that includes all pre-requisite knowledge, augmented with step-by-step explanations of more advanced concepts. The Handbook of Granular Computing represents a significant and valuable contribution to the literature and will appeal to a broad audience including researchers, students and practitioners in the fields of Computational Intelligence, pattern recognition, fuzzy sets and neural networks, system modelling, operations research and bioinformatics.

Neural Networks and Soft Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 9783790800050
Total Pages : 940 pages
Book Rating : 4.8/5 ( download)

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Book Synopsis Neural Networks and Soft Computing by : Leszek Rutkowski

Download or read book Neural Networks and Soft Computing written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2003-02-12 with total page 940 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.