DocumentCode :
31881
Title :
Simulating Dynamic Plastic Continuous Neural Networks by Finite Elements
Author :
Joghataie, Abdolreza ; Torghabehi, Omid Oliyan
Author_Institution :
Civil Eng. Dept., Sharif Univ. of Technol., Tehran, Iran
Volume :
25
Issue :
8
fYear :
2014
fDate :
Aug. 2014
Firstpage :
1583
Lastpage :
1587
Abstract :
We introduce dynamic plastic continuous neural network (DPCNN), which is comprised of neurons distributed in a nonlinear plastic medium where wire-like connections of neural networks are replaced with the continuous medium. We use finite element method to model the dynamic phenomenon of information processing within the DPCNNs. During the training, instead of weights, the properties of the continuous material at its different locations and some properties of neurons are modified. Input and output can be vectors and/or continuous functions over lines and/or areas. Delay and feedback from neurons to themselves and from outputs occur in the DPCNNs. We model a simple form of the DPCNN where the medium is a rectangular plate of bilinear material, and the neurons continuously fire a signal, which is a function of the horizontal displacement.
Keywords :
finite element analysis; neural nets; DPCNN; bilinear material; continuous material; dynamic plastic continuous neural networks; feedback; finite element method; nonlinear plastic medium; wire-like connections; Biological neural networks; Neurons; Plastics; Strain; Stress; Training; Finite element; neural networks; numerical modeling; wave propagation; wave propagation.;
fLanguage :
English
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2162-237X
Type :
jour
DOI :
10.1109/TNNLS.2013.2294315
Filename :
6687302
Link To Document :
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