Multidimensional Wavelet Networks Based on a Tensor Product Structure
基于张量积结构的多维小波网络（英文）

Based on the wavelet frame theory, a novel wavelet network for function learning in multidimensional spaces is proposed to avoid the 'curse of dimensionality'. The main feature of the proposed wavelet network is to multiply the reconstruction of each dimension in the output layer instead of adding them as usual. Thus a multidimensional wavelet frame will be generated automatically for approximation, and function learning can be realized through online or off-line adjustment of corresponding weight coefficients. Design methods for one_dimensional wavelet networks can also be generalized straightforwardly to multidimensional cases by using the tensor product structure. In the experiments, the multidimensional wavelet network performs well.