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308 Seiten; 9780471495178.3 Gewicht in Gramm: 1. N° de réf. du vendeur 526662
Durch die Anwendung rückbezüglicher neuronaler Netze läßt sich die Leistungsfähigkeit konventioneller Technologien der digitalen Datenverarbeitung signifikant erhöhen. Von besonderer Bedeutung ist dies für komplexe Aufgaben, wie z.B. die mobile Kommunikation, die Robotik und die Medizintechnik. Das Buch faßt Originalarbeiten zur Stabilität neuronaler Netze zusammen und verbindet streng mathematische Analysen mit anschaulichen Anwendungen und experimentellen Belegen.
À propos de l?auteur:
Danilo Mandic from the Imperial College London, London, UK was named Fellow of the Institute of Electrical and Electronics Engineers in 2013 for contributions to multivariate and nonlinear learning systems.
Jonathon A. Chambers is the author of Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability, published by Wiley.
Titre : Recurrent Neural Networks for Prediction: ...
Éditeur : John Wiley & Sons
Date d'édition : 2001
Reliure : hardcover
Etat : Gut
Vendeur : Vulkaneifel Bücher, Birgel, Allemagne
hardcover. Etat : Sehr gut. Buch ist leicht verlagert (längs durchgebogen), kleine Lagerspuren am Buch, Inhalt einwandfrei und ungelesen 238113 Sprache: Englisch Gewicht in Gramm: 740. N° de réf. du vendeur 219249
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Vendeur : Corner of a Foreign Field, Tokyo, TOKYO, Japon
Hardcover. Etat : Very Good. No Jacket. 1st Edition. 2001.Hardcover.Very good condition.285 pages.Ships from Japan.Usually ships in 1-2 working days. N° de réf. du vendeur 384501
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Vendeur : BennettBooksLtd, San Diego, NV, Etats-Unis
hardcover. Etat : New. In shrink wrap. Looks like an interesting title! N° de réf. du vendeur Q-0471495174
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Vendeur : HPB-Red, Dallas, TX, Etats-Unis
Hardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_372094938
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Vendeur : Phatpocket Limited, Waltham Abbey, HERTS, Royaume-Uni
Etat : Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. N° de réf. du vendeur Z1-B-023-02413
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 33152-n
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur FW-9780471495178
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 33152-n
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 33152
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) can be implemented to expand the range of traditional signal processing techniques and to help combat the problem of prediction. Within this text neural networks are considered as massively interconnected nonlinear adaptive filters. Analyses the relationships between RNNs and various nonlinear models and filters, and introduces spatio-temporal architectures together with the concepts of modularity and nestingExamines stability and relaxation within RNNsPresents on-line learning algorithms for nonlinear adaptive filters and introduces new paradigms which exploit the concepts of a priori and a posteriori errors, data-reusing adaptation, and normalisationStudies convergence and stability of on-line learning algorithms based upon optimisation techniques such as contraction mapping and fixed point iterationDescribes strategies for the exploitation of inherent relationships between parameters in RNNsDiscusses practical issues such as predictability and nonlinearity detecting and includes several practical applications in areas such as air pollutant modelling and prediction, attractor discovery and chaos, ECG signal processing, and speech processing Recurrent Neural Networks for Prediction offers a new insight into the learning algorithms, architectures and stability of recurrent neural networks and, consequently, will have instant appeal. It provides an extensive background for researchers, academics and postgraduates enabling them to apply such networks in new applications. VISIT OUR COMMUNICATIONS TECHNOLOGY WEBSITE! VISIT OUR WEB PAGE! / Neural networks consist of interconnected groups of neurones which function as processing units. Through the application of neural networks, the capabilities of conventional digital signal processing techniques can be significantly enhanced to meet the demands of new technologies such as mobile communications, robotics and medical instrumentation. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780471495178
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