Adaptive bilinear inverse filtering

A parsimonious adaptive nonlinear filtering structure based on bilinear models is presented. A state-dependent embedding for developing nonlinear filters is presented. It is used to develop a computationally efficient bilinear adaptive filter which requires only local adaptation. Modularity and local connectivity make the structure amenable to VLSI implementation. In contrast to previous input-output pair (system identification) frameworks, an inverse filtering problem is considered where only output is observable. The adaptation is shown to be dependent on both past and present gradients