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