Neural Networks Theory

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Neural Networks Theory

Author: Alexander I. Galushkin
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-10-29
This book, written by a leader in neural network theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization. It details more than 40 years of Soviet and Russian neural network research and presents a systematized methodology of neural networks synthesis. The theory is expansive: covering not just traditional topics such as network architecture but also neural continua in function spaces as well.
The Principles of Deep Learning Theory

Author: Daniel A. Roberts
language: en
Publisher: Cambridge University Press
Release Date: 2022-05-26
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Process Neural Networks

Author: Xingui He
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-07-05
"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 mapping relationship between the input and output of traditional neural networks and enhances the expression capability for practical problems, with broad applicability to solving problems relating to processes in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are closely examined. The application methods, network construction principles, and optimization algorithms of process neural networks in practical fields, such as nonlinear time-varying system modeling, process signal pattern recognition, dynamic system identification, and process forecast, are discussed in detail. The information processing flow and the mapping relationship between inputs and outputs of process neural networks are richly illustrated. Xingui He is a member of Chinese Academy of Engineering and also a professor at the School of Electronic Engineering and Computer Science, Peking University, China, where Shaohua Xu also serves as a professor.