[1]YE Tao,ZHU Xue-feng.Theoretical discussion on the process neural network the ory[J].CAAI Transactions on Intelligent Systems,2007,2(5):1-6.
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Theoretical discussion on the process neural network the ory

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 2 Number of periods: 2007 5 Page number: 1-6 Column: 综述 Public date: 2007-10-25
Title:
Theoretical discussion on the process neural network the ory
Author(s):
YE Tao;  ZHU Xue-feng
College of Automation Science and Engineering, South China University of Technol ogy, Guangzhou 510641, China
Keywords:
artificial neural networks;  process neuron;  function orthogonal basis;  Fourier s eries;  feature expansion
CLC:
TP183
DOI:
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Abstract:
Process neural networks (PNNs) are networks suitable for processing signal input , whose elementary unit is the process neuron, a newly developed neuron model. T he process neuron is different from traditional neurons in nature, but there is an inherent relationship between them. The former can be infinitely approached b y the latter with arbitrary precision. Two theorems are presented and proved in this paper, giving two models for approaching corresponding process neurons:the timedomain feature expansion model and the　orthogonal decomposition feature e xpansion model. And two corollaries are given based on the second theorem. Final ly, some problems with PNNs are discussed and several research topics suggested. The conclusions are significant to theoretical research on process neurons and PNNs.
References:
［1】 HAGAN M T, DEMUTH H B, BEALE M. Neural network design ［M］. Boston: PWS P ublishing Company, 1996.
［2］HORNIK K M,STINCHCOMBE M,WHITE H.Multilayer feedforward networks are un iversal approximators ［J］. Neural Networks, 1989, 2(5): 359-366.
［3］何新贵，梁久祯. 过程神经元网络的若干理论问题［J］. 中国工程科学, 200 0, 2(12): 40-44.
?HE Xingui, LIANG Jiuzhen. Some theoretical issues on procedure neural networks ［J］. Engineering Science, 2000, 2(12): 40-44.
［4］许少华，何新贵. 基于函数正交基展开的过程神经网络学习算法［J］. 计算机学报, 2004, 27(5): 645-650.
?XU Shaohua, HE Xingui. Learning algorithms of process neural networks based on o rthogonal function basis expansion ［J］. Chinese Journal of Computers, 2004, 27 (5): 645-650.
［5］丁 刚，钟诗胜. 基于过程神经网络的热平衡温度预测研究［J］. 宇航学报, 2006, 27(3): 489-492.
?DING Gang, ZHONG Shisheng. Thermal equilibrium temperature prediction based on p rocess neural network ［J］. Journal of Astronautics, 2006, 27(3): 489-492.
 ［6］何新贵，许少华. 输入输出均为时变函数的过程神经网络及应用［J］. 软件学报, 2003, 14(4): 764-769.
?HE Xingui, XU Shaohua. Process neural network with timevaried input and output functions and its applications ［J］. Journal of Software, 2003, 14(4): 764-769.
［7］柳重堪. 正交函数及其应用［M］. 北京: 国防工业出版社, 1982.
［8］赵录怀，高金峰，刘崇新，等. 信号与系统分析［M］. 北京: 高等教育出版社, 2003 .
［9］何新贵，许少华. 一类反馈过程神经元网络模型及其学习算法［J］. 自动化学报, 2004, 30(6): 801-806.
?HE Xingui, XU Shaohua. A feedback process neural network model and its learning algorithm ［J］. Acta Automatica Sinica, 2004, 30(6): 801-806
［10］何新贵，许少华. 过程神经元网络及其在时变信息处理中的应用［J］. 智能系统学报, 2006, 1(1): 1-8.
?HE Xingui, XU Shaohua. Process neural networks and its applications in timevar y ing information processing ［J］. CAAI Trans on Intelligent Systems, 2006, 1(1) : 1-8.
［11］许少华，何新贵，刘 坤，等. 关于连续过程神经元网络的一些理论问题［J ］. 电子学报, 2006, 34(10): 1838-1841.
XU Shaohua, HE Xingui, LIU Kun，et al. Some theoretical issues on continuous pro c ess neural networks ［J］. Acta Electronica Sinica, 2006, 34(10): 1838-1841.
［12］胡广书. 现代信号处理教程［M］. 北京: 清华大学出版社, 2004.
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