Nonlinear blind deconvolution based on a state-space model

This paper proposes a nonlinear independent component analysis method using a state-space model to solve a nonlinear blind deconvolution problem. The proposed algorithm is derived based on the property that the probability density function of the output of the model only depends on that of the input and the direct feedthrough term of the model. Moreover, since many systems such as mechanical systems do not have any direct feedthrough term, we extend the proposed algorithm to systems without direct feedthrough terms. Furthermore, a numerical simulation demonstrates the effectiveness of the proposed method