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Process Neural Networks

Theory and Applications

  • Xingui He
  • Shaohua Xu

Part of the Advanced Topics in Science and Technology in China book series (ATSTC)

Table of contents

About this book

Introduction

"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.

Keywords

ATSTC Artificial Neural Networks Pattern Recognition Process Control Signal Processing System Identification ZJUP algorithms artificial neural network cognition learning modeling neural network optimization system modeling

Authors and affiliations

  • Xingui He
    • 1
  • Shaohua Xu
    • 1
  1. 1.School of Electronic Engineering and Computer SciencePeking UniversityBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-73762-9
  • Copyright Information Springer-Verlag Berlin Heidelberg 2010
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-73761-2
  • Online ISBN 978-3-540-73762-9
  • Series Print ISSN 1995-6819
  • Buy this book on publisher's site