DocumentCode :
2649431
Title :
An application-specific array architecture for feedforward with backpropagation ANNs
Author :
Malluhi, Q.M. ; Bayoumi, M.A. ; Rao, T.R.N.
Author_Institution :
Center for Adv. Comput. Studies, Univ. of Southwestern Louisiana, Lafayette, LA, USA
fYear :
1993
fDate :
25-27 Oct 1993
Firstpage :
333
Lastpage :
344
Abstract :
An application-specific array architecture for Artificial Neural Networks (ANNs) computation is proposed. This array is configured as a mesh-of-appendixed-trees (MAT). Algorithms to implement both the recall and the training phases of the multilayer feedforward with backpropagation ANN model are developed on MAT. The proposed MAT architecture requires only O(log N) time, while other reported techniques offer O(N) time, where N is the size of the largest layer. Beside the high speed performance, pipelining of more than one input pattern can be achieved which further improves the performance
Keywords :
application specific integrated circuits; backpropagation; feedforward neural nets; neural chips; parallel architectures; pipeline processing; application-specific array architecture; backpropagation ANNs; feedforward; high speed performance; input pattern; mesh-of-appendixed-trees; multilayer feedforward; pipelining; training phases; Artificial neural networks; Backpropagation; Computational modeling; Computer architecture; Computer networks; Concurrent computing; Neural networks; Neurons; Parallel processing; Pipeline processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Application-Specific Array Processors, 1993. Proceedings., International Conference on
Conference_Location :
Venice
ISSN :
1063-6862
Print_ISBN :
0-8186-3492-8
Type :
conf
DOI :
10.1109/ASAP.1993.397156
Filename :
397156
Link To Document :
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