DocumentCode
2228338
Title
Modular neural networks for solving high complexity tasks
Author
El-Bakry, Hazem M. ; Abo-Elsoud, M.A. ; Kamel, M.S.
Author_Institution
Fac. of Comput. Sci. & Inf. Syst., Mansoura Univ., Egypt
Volume
3
fYear
2000
fDate
2000
Firstpage
555
Abstract
In this paper, we introduce a powerful solution for complex problems which are required to be solved using neural nets. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such an approach is applied to implement XOR functions, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non-modular designs, a salient reduction in the order of computations and hardware requirements is obtained
Keywords
logic gates; multiplying circuits; neural nets; pattern classification; XOR functions; digital multiplier; hardware requirements; high complexity tasks; homogenous regions; input space; logic functions; modular neural networks; nonmodular designs; Artificial neural networks; Computer architecture; Computer science; Information systems; Interference; Logic functions; Multi-layer neural network; Neural networks; Neurons; Power engineering and energy;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
Conference_Location
Geneva
Print_ISBN
0-7803-5482-6
Type
conf
DOI
10.1109/ISCAS.2000.856120
Filename
856120
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