Fuzzy mixtures of complementary local experts: towards neuro-fuzzy modular networks

This paper describes our empirical study in neuro-fuzzy modeling for a real-world nonlinear regression application "multi-illuminant color reproduction for electric cameras", investigating a variety of neuro-fuzzy architectures. We explain all those models in the complementary modular network framework, demonstrating several representative models, and discuss strengths and weaknesses of individual models. In particular, we emphasize usefulness of neuro-fuzzy modular networks especially when the posed regression task requires multiple inputs and outputs with a small number of training data due to efficient practical implementation