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.
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