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A Volterra series is a basic tool in the non-parametric approach to the nonlinear systems modelling, which posses a facility of approximating a large family of such systems, including an important subclass of block-oriented structures. In this paper we investigate a Volterra representation of the Wiener system and study an upper bound of an error arising from reducing the model's order as well as...
In the note we examine the recently introduced aggregation modeling technique in a system identification context. First, we show that its finite sample size properties are preserved for any nonlinear SISO system with finite memory. Then, using as an example the peripheral auditory model we demonstrate that it allows to find effective Volterra approximations of LNL systems.
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