Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system; neural networks provide a model-free… Mehr…
Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system; neural networks provide a model-free, adaptive, parallel-processing solution. Neural Networks in a Softcomputing Framework presents a thorough review of the most popular neural-network methods and their associated techniques. This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model. Neural Networks in a Softcomputing Framework is an ideal textbook for graduate students and researchers in this field because in addition to grasping the fundamentals, they can discover the most recent advances in each of the popular models. The systematic survey of each neural-network model and the exhaustive list of references will enable researchers and students to find suitable topics for future research. The important algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. Buch (fremdspr.) Ke-Lin Du#M.N.S. Swamy Taschenbuch, Springer London, 13.10.2010, Springer London, 2010<
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[EAN: 9781849965743], Neubuch, [SC: 0.0], [PU: Springer London], EVOLUTIONARYCOMPUTATION; FUZZYSYSTEMS; NEURALNETWORKS; OPTIMIZATION; PATTERNRECOGNITION; SIGNALPROCESSING; ARTIFICIALINTELLIGENCE; FUZZYLOGIC; FUZZYSYSTEM; NEURO-FUZZYSYSTEMS, Druck auf Anfrage Neuware - Printed after ordering - This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms - powerful tools for neural-network learning - are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. 620 pp. Englisch, Books<
This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important m… Mehr…
This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms – powerful tools for neural-network learning – are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. New Textbooks>Trade Paperback>Science>Engineering>Engr Ref, Springer London Core >1 >T<
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Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system; neural networks provide a model-free… Mehr…
Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system; neural networks provide a model-free, adaptive, parallel-processing solution. Neural Networks in a Softcomputing Framework presents a thorough review of the most popular neural-network methods and their associated techniques. This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model. Neural Networks in a Softcomputing Framework is an ideal textbook for graduate students and researchers in this field because in addition to grasping the fundamentals, they can discover the most recent advances in each of the popular models. The systematic survey of each neural-network model and the exhaustive list of references will enable researchers and students to find suitable topics for future research. The important algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. Buch (fremdspr.) Ke-Lin Du#M.N.S. Swamy Taschenbuch, Springer London, 13.10.2010, Springer London, 2010<
Nr. 25606603. Versandkosten:, Lieferbar in 2 - 3 Tage, DE. (EUR 0.00)
[EAN: 9781849965743], Neubuch, [SC: 0.0], [PU: Springer London], EVOLUTIONARYCOMPUTATION; FUZZYSYSTEMS; NEURALNETWORKS; OPTIMIZATION; PATTERNRECOGNITION; SIGNALPROCESSING; ARTIFICIALINTELLIGENCE; FUZZYLOGIC; FUZZYSYSTEM; NEURO-FUZZYSYSTEMS, Druck auf Anfrage Neuware - Printed after ordering - This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms - powerful tools for neural-network learning - are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. 620 pp. Englisch, Books<
This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important m… Mehr…
This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms – powerful tools for neural-network learning – are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence. New Textbooks>Trade Paperback>Science>Engineering>Engr Ref, Springer London Core >1 >T<
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This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms - powerful tools for neural-network learning - are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence.
Detailangaben zum Buch - Neural Networks in a Softcomputing Framework Ke-Lin Du Author
EAN (ISBN-13): 9781849965743 ISBN (ISBN-10): 1849965749 Gebundene Ausgabe Taschenbuch Erscheinungsjahr: 2010 Herausgeber: Springer London Core >1 >T 620 Seiten Gewicht: 0,923 kg Sprache: eng/Englisch
Buch in der Datenbank seit 2012-06-05T15:34:52+02:00 (Vienna) Detailseite zuletzt geändert am 2024-01-31T14:42:23+01:00 (Vienna) ISBN/EAN: 1849965749
ISBN - alternative Schreibweisen: 1-84996-574-9, 978-1-84996-574-3 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: swamy, lin Titel des Buches: lin, neural networks
Daten vom Verlag:
Autor/in: Ke-Lin Du; M.N.S. Swamy Titel: Neural Networks in a Softcomputing Framework Verlag: Springer; Springer London 566 Seiten Erscheinungsjahr: 2010-10-13 London; GB Gedruckt / Hergestellt in Niederlande. Sprache: Englisch 53,49 € (DE) 54,99 € (AT) 59,00 CHF (CH) POD L, 566 p.
BC; Hardcover, Softcover / Technik/Allgemeines, Lexika; Künstliche Intelligenz; Verstehen; Evolutionary Computation; Fuzzy Systems; Neural Networks; Optimization; Pattern Recognition; Signal Processing; artificial intelligence; fuzzy logic; fuzzy system; neuro-fuzzy systems; Computational Intelligence; Complex Systems; Theory of Computation; Artificial Intelligence; Signal, Speech and Image Processing; Automated Pattern Recognition; Kybernetik und Systemtheorie; Theoretische Informatik; Elektronik; Digitale Signalverarbeitung (DSP); Mustererkennung; BB; EA
Fundamentals of Machine Learning and Softcomputing.- Multilayer Perceptrons.- Hopfield Networks and Boltzmann Machines.- Competitive Learning and Clustering.- Radial Basis Function Networks.- Principal Component Analysis Networks.- Fuzzy Logic and Neurofuzzy Systems.- Evolutionary Algorithms and Evolving Neural Networks.- Discussion and Outlook. Provides a powerful and universal paradigm for information processing Provides state-of-the-art descriptions of the important major research results of the respective neural methods Dicusses array signal processing problems in order to illustrate the applications of each neural model
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