A Genetic Algorithm for Constructing Wavelet Neural Networks
In this paper, a new algorithm is proposed for the design of WNNs. The design is performed in an evolutionary way, which allowed us to construct a parsimonious model to satisfy the design requirement. A genetic algorithm (GA) is used to select a wavelet basis, and the fitness of a wavelet is evaluated according to the residue reduction. Output weights are updated using least square techniques. Simulations demonstrate the effectiveness of the proposed algorithm.
Unable to display preview. Download preview PDF.