Orthogonal functional basis method for function approximation

摘要

An orthogonal functional basis method for function approximation is disclosed. Starting with the orthogonal least squares method, a new subset selection method for selecting a set of appropriate basis functions is explained where, instead of picking a subset from a given functional basis, the subset is selected from a combination of functional basis evolved from a set of heterogeneous basis functions. The method results in a more efficient neural network.