Adaptive prediction using fuzzy systems and neural networks
Jeffrey T. Spooner, Kevin M. Passino · 1997
A collection of adaptive prediction schemes which use the functional approximation properties of fuzzy systems is presented. Both direct and indirect approaches are developed using gradient and least squares update laws. It is proven that the prediction error converges asymptotically to zero for each case provided some minor assumptions hold.