PROCEEDINGS OF THE IEEE WORKSHOP ON NNSP PP Blind Deconvolution Equalization Using State Space Models

In this paper we propose extension of multichannel blind equalization problem as suming that both mixing and demixing models are described by stable linear state space systems The problem is formulated as an optimization task New learning algorithms are developed which can be considered as extension of existing algorithms By applying demixing state space model we will be able to reduce complexity of separating systems in some practical implementations