Two-pass orthogonal least-squares algorithm to train and reduce fuzzy logic systems

Fuzzy logic systems (FLSs) can be designed using training data (i.e. given M numerical input/output pairs) and supervised learning algorithms. Orthogonal least-squares (OLS) learning decomposes a FLS into a linear combination of M/sub s/>