Title :
Modular neural networks for solving high complexity problems
Author :
El-Bakry, Hazem M. ; Abo-Elsoud, M.A. ; Kame, M.S.
Author_Institution :
Fac. of Comput. Sci. & Inf. Syst., Mansoura Univ., Egypt
Abstract :
In this paper, we introduce a powerful solution for complex problems which 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 a 2-bit digital multiplier. Compared to previous nonmodular designs, a salient reduction in the order of computations and hardware requirements is obtained
Keywords :
computational complexity; logic CAD; logic gates; logic simulation; multiplying circuits; neural nets; problem solving; 1 bit; 2 bit; MNNs; XOR function; complex problems; computations; digital multiplier implementation; hardware requirements; high complexity problem solving; homogenous regions; input space division; logic function implementation; modular neural nets; modular neural networks; neural nets; nonmodular design; Artificial neural networks; Computer architecture; Computer science; Decision making; Information systems; Interference; Logic functions; Multi-layer neural network; Neural networks; Neurons;
Conference_Titel :
Microelectronics, 2000. ICM 2000. Proceedings of the 12th International Conference on
Conference_Location :
Tehran
Print_ISBN :
964-360-057-2
DOI :
10.1109/ICM.2000.916448
