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In this chapter, we introduce a powerful solution for complex problems that are required to be solved by using neural nets. This is done by using modular neural nets (MNNs) that di‐ vide the input space into several homogenous regions. Such approach is applied to imple‐ ment XOR functions, 16 logic function on one bit level, and 2-bit digital multiplier. Compared to previous nonmodular designs, a salient reduction in the order of computa‐ tions and hardware requirements is obtained.

Integrating Modularity and Reconfigurability for Perfect Implementation of Neural Networks