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" Toward deep neural networks : "
Yunong Zhang, Dechao Chen, Chengxu Ye
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BL
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| Record Number
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841909
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| Main Entry
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Zhang, Yunong
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| Title & Author
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Toward deep neural networks : : WASD neuronet models, algorithms, and applications /\ Yunong Zhang, Dechao Chen, Chengxu Ye
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| Publication Statement
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Boca Raton, Florida :: CRC Press,, [2019]
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, ©2019
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| Series Statement
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Chapman & Hall/CRC artificial intelligence and robotics series
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| Page. NO
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1 online resource (xxv, 342 pages)
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| ISBN
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0429426445
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: 0429760973
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: 0429760981
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: 042976099X
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: 9780429426445
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: 9780429760976
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: 9780429760983
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: 9780429760990
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1138387037
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9781138387034
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| Bibliographies/Indexes
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Includes bibliographical references and index
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| Contents
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Single-input Euler-polynomial WASD neuronet -- Single-input Bernoulli-polynomial WASD neuronet -- Single-input Laguerre-polynomial WASD neuronet -- Two-input Legendre-polynomial WASD neuronet -- Two-input Chebyshev-polynomial-of-class-1 WASD neuronet -- Two-input Chebyshev-polynomial-of-class-2 WASD neuronet -- Three-input Euler-polynomial WASD neuronet -- Three-input Power-activation WASD neuronet -- Multi-input Euler-polynomial WASD neuronet -- Multi-input Bernoulli-polynomial WASD neuronet -- Multi-input Hermite-polynomial WASD neuronet -- Multi-input sine-activation WASD neuronet -- Application to Asian population prediction -- Application to European population prediction -- Application to Oceanian population prediction -- Application to Northern American population prediction -- Application to Indian subcontinent population prediction -- Application to world population prediction -- Application to Russian population prediction -- WASD neuronet versus BP neuronet applied to Russian population prediction -- Application to Chinese population prediction -- WASD neuronet versus BP neuronet applied to Chinese population prediction -- Application to USPD prediction -- Application to time series prediction -- Application to GFR estimation
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| Abstract
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Toward Deep Neural Networks: WASD Neuronet Models, Algorithms, and Applications introduces the outlook and extension toward deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors' 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet, and allows reader to extend the techniques in the book to solve scientific and engineering problems. The book will be of interest to engineers, senior undergraduates, postgraduates, and researchers in the fields of neuronets, computer mathematics, computer science, artificial intelligence, numerical algorithms, optimization, simulation and modeling, deep learning, and data mining. Features Focuses on neuronet models, algorithms, and applications Designs, constructs, develops, analyzes, simulates and compares various WASD neuronet models, such as single-input WASD neuronet models, two-input WASD neuronet models, three-input WASD neuronet models, and general multi-input WASD neuronet models for function data approximations Includes real-world applications, such as population prediction Provides complete mathematical foundations, such as Weierstrass approximation, Bernstein polynomial approximation, Taylor polynomial approximation, and multivariate function approximation, exploring the close integration of mathematics (i.e., function approximation theories) and computers (e.g., computer algorithms) Utilizes the authors' 20 years of research on neuronets
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Neural networks (Computer science)
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BUSINESS ECONOMICS / Statistics
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COMPUTERS / General
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COMPUTERS / Machine Theory
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Neural networks (Computer science)
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| Dewey Classification
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006.3/2
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| LC Classification
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QA76.87.Z47537 2019eb
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| Added Entry
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Chen, Dechao
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Ye, Chengxu
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