Using wavelet network in nonparametric estimation
IEEE Transactions on Neural Networks
Tuning of the structure and parameters of a neural network using an improved genetic algorithm
IEEE Transactions on Neural Networks
Mutation-based genetic neural network
IEEE Transactions on Neural Networks
A new class of wavelet networks for nonlinear system identification
IEEE Transactions on Neural Networks
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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.