Identification of iage using multiwavelet and neural network

Abstract EN

A model of multiwavelet-based neural networks is proposed.

Its universal and L2 approximation properties, together with its consistency are proved, and the convergence rates associated with these properties are estimated.

The structure of this network is similar to that of the wavelet network, except that the orthonormal scaling functions are replaced by orthonormal multiskilling functions.

The theoretical analyses show that the multiwavelet network converges more rapidly than the wavelet network, especially for smooth functions.

To make a comparison between both networks, experiments are carried out with the Daubechies2 wavelet network and the GHM multiwavelet network, and the results support the theoretical analysis well.

In addition, the results also illustrate that at the jump discontinuities, the approximation performance of the two networks are about the same.