Nonlinear dynamic method to suppress reverberation based on RBF neural networks

On condition that the noise, such as the reverberation, could be modeled as a dynamical model with lower dimensions, it would be picked out from its mixture with a useful signal by using the nonlinear dynamic method proposed in this paper. In other words, the useful signal could be separated from the noise with this method, which constructs the nonlinear inverse to linear filter, based on the spectrum difference between the noise and the useful signal, in virtue of successive approximation with Radial Basis Function Neural Networks. Two examples, with the sine pulse as the useful signal, are displayed. The artificial chaotic signal plays the role of the noise in one example, and the actual reverberation in another. These examples confirm the feasibility of this method.