DocumentCode
1748946
Title
Adaptive resonance theory networks using incremental communication
Author
Chen, Ming ; Ghorbani, Ali A. ; Bhavsar, Virendra C.
Author_Institution
Fac. of Comput. Sci., New Brunswick Univ., Fredericton, NB, Canada
Volume
4
fYear
2001
fDate
2001
Firstpage
2774
Abstract
The incremental inter-node communication method is applied to the adaptive resonance theory 2 (ART2) networks. The incremental communication is aimed at reducing the communication costs of parallel and VLSI implementations of artificial neural networks. An ART2 node architecture incorporating the incremental communication is presented. A simulator is developed to study the behavior of ART2 networks with varying precisions of incremental data communication. Experiments are carried out to study the effects of the incremental communication on the convergence and savings in communication costs. We have found that even 7-bit precision in fixed-point and 13-bit (including 8-bit exponent) floating-point representations may be sufficient for the network to give the same results as those with conventional communication using 32-bit precision. The simulation results show that the limited precision errors are bounded and do not seriously affect the convergence of ART2 networks
Keywords
ART neural nets; communication complexity; convergence; 13 bit; 32 bit; 7 bit; 8 bit; ART neural networks; ART2 networks; ART2 node architecture; VLSI implementations; adaptive resonance theory 2 networks; communication costs; convergence; incremental inter-node communication; parallel implementations; Adaptive systems; Artificial neural networks; Computational modeling; Computer science; Convergence; Costs; Data communication; Niobium; Resonance; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.938812
Filename
938812
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