Growing-type weights and structure determination of 2-input Legendre orthogonal polynomial neuronet

In order to remedy the weaknesses of conventional back-propagation (BP) neuronets, a novel 2-input Legendre orthogonal polynomial neuronet (2ILOPN) based on the theory of the multivariate function approximation is constructed and investigated in this paper. In addition, based on the weights-direct-determination (WDD) method, two weights-and-structure-determination (WASD) algorithms with different growing speeds are built up to determine the optimal weights and structure of the proposed 2ILOPN. Numerical-study results further verify the efficacy of the proposed 2ILOPN equipped with the two aforementioned WASD algorithms.