A Noval Algorithm for Optimizing Wavelet Networks and Its Application

Itpsilas an important problem to optimize structure and parameters of wavelet network. In this paper, a new filled function and a novel global optimization technique in which combines this filled function method and BP algorithm are presented to optimize wavelet network efficiently. In this algorithm, the BP algorithm finds one of local minimal points first, the filled function method finds the point that is lower than the minimal point previously found. By repeating these processes, a global minimal point can be obtained at last. Compared with usual BP training algorithm, this new global optimization algorithm is more efficient and has a higher accuracy in application to three kinds of common faults diagnosis of flight control system.