Complexity Minimalization of Nonsingleton-based Fuzzy-Neural Network
Kin Fong Lei, Péter Bárányi, Yeung Yam · Journal of Advanced Computational Intelligence and Intelligent Informatics · 2000
Singular value based reduction has been proposed for a singleton-based generalized neural network that is general in the sense that singleton-consequent-based fuzzy logic function generators are applied to define nonlinear weighting functions on connections among neurons. The product-sum-gravity inference technique with singleton consequent defines piece-wise linear approximation of nonlinear weighting functions. This paper proposed the use of nonsingleton-consequent-based product-sumgravity fuzzy algorithm that results in a piece-wise nonlinear approximation of weighting functions that considerably improve the approximation properties of the generalized network. This network is called a nonsingleton-based generalized neural network. The main objective of this technical report is to introduce the extension of the singular value based reduction technique to the nonsingleton-based neural network.