Process Neural Networks

Process Neural Networks
Author: Xingui He
Publisher: Springer Science & Business Media
Total Pages: 240
Release: 2010-07-05
Genre: Computers
ISBN: 3540737626

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For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.


Process Neural Networks
Language: en
Pages: 240
Authors: Xingui He
Categories: Computers
Type: BOOK - Published: 2010-07-05 - Publisher: Springer Science & Business Media

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For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping
Process Neural Networks
Language: en
Pages:
Authors: Xingui He
Categories:
Type: BOOK - Published: 2010 - Publisher:

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"Process Neural Network: Theory and Applications" proposes the concept and model of a process neural network for the first time, showing how it expands the mapp
Efficient Processing of Deep Neural Networks
Language: en
Pages: 254
Authors: Vivienne Sze
Categories: Technology & Engineering
Type: BOOK - Published: 2022-05-31 - Publisher: Springer Nature

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This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are curren
Applied Neural Networks for Signal Processing
Language: en
Pages: 388
Authors: Fa-Long Luo
Categories: Computers
Type: BOOK - Published: 1998 - Publisher: Cambridge University Press

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A comprehensive introduction to the use of neural networks in signal processing.
Multivariate Statistical Machine Learning Methods for Genomic Prediction
Language: en
Pages: 707
Authors: Osval Antonio Montesinos López
Categories: Technology & Engineering
Type: BOOK - Published: 2022-02-14 - Publisher: Springer Nature

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This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statis