Nonlinear State Space Models – Semi‐Blind Signal Processing
Andrzej S Cichocki, Шун-ичи Амари · 2002
In this chapter we attempt to extend and generalize the results discussed in the previous chapters to nonlinear dynamical models. However, the problem is not only very challenging but intractable in the general case without a priori knowledge about the mixing and filtering nonlinear process. Therefore, in this chapter we consider very briefly only some simplified nonlinear models. In addition, we assume that some information about the mixing and separating system and source signals is available. In practice, special nonlinear dynamical models are considered in order to simplify the problem and solve it efficiently for specific applications. Specific examples include the Wiener model, the Hammerstein model and Nonlinear Autoregressive Moving Average models.