DocumentCode :
2871531
Title :
Recognition of effective algorithm using a higher order multi-layer neural networks
Author :
Junwen, Gao ; Jiancheng, Liu
Author_Institution :
Electron. Dept., Guangdong Agric.-Ind.-Bus. Polytech. Coll., Guangzhou, China
Volume :
9
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
A new neural network architecture, call a higher order multi-layer neural networks(HOMLNN) is presented. The architecture of an HOMLNN is a modified model of the Evolved functional neural network(EFNN)with a hidden layer which is composed of self-evolve neurons and additional multiplication inputs between conventional inputs and self-evolve neurons. The authors drive a generalized dynamic backpropagation algorithm and show a new approach to the Recognition of dynamical systems by means of HOMLNN. Experiment result showed that the method is effective for the Recognition of dynamical systems.
Keywords :
backpropagation; neural nets; EFNN; HOMLNN; dynamic backpropagation algorithm; effective algorithm recognition; evolved functional neural network; higher order multilayer neural networks; self evolve neurons; Artificial neural networks; Delay; Equalizers; Feedforward neural networks; Heuristic algorithms; Neurons; Nonlinear dynamical systems; Algorithm; dynamical systems; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5623052
Filename :
5623052
Link To Document :
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