Topic
Volterra series
About: Volterra series is a research topic. Over the lifetime, 2731 publications have been published within this topic receiving 46199 citations.
Papers published on a yearly basis
Papers
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22 Mar 2006
TL;DR: In this article, a novel identification method for time-varying Volterra systems (TVVS) is proposed, where the system identification problem is converted to a state estimation problem of a dynamic system.
Abstract: Most nonlinear system identification methods based on Volterra model assume that the underlying system is time-invariant. In this paper, a novel identification method for time-varying Volterra systems (TVVS) is proposed. We view this problem from a different perspective in the sense that the system identification problem is converted to a state estimation problem of a dynamic system. The time-varying Volterra kernels are governed by a Gauss-Markov stochastic difference equation upon which a state-space representation of time-varying Volterra systems is built. The state transition matrix and noise covariance of the underlying state equations are usually unknown. Therefore, we develop a method to estimate these unknown quantities. Finally, a Kalman filtering scheme is utilized to identify and track the time-varying Volterra system. Simulation examples are given to illustrate the better performance of the proposed method as compared with other adaptive identification methods such as the LMS and RLS algorithms.
12 citations
TL;DR: In this paper, a new recursive algorithm for the computation of the gain bounds for the generalized frequency response functions of the polynomial nonlinear autoregressive model with exogenous input is proposed, and effective procedures for the practical computations of the new bound are developed.
Abstract: In Part 1 of this paper the concept of a bound for the output frequency response magnitude characteristics of nonlinear systems was proposed, and general calculation and analysis procedures were developed. In this, Part 2 of the paper, a new recursive algorithm for the computation of the gain bounds for the generalized frequency response functions of the polynomial nonlinear autoregressive model with exogenous input is proposed, and effective procedures for the practical computation of the new bound are developed. Simulated examples are included to verify the effectiveness of the proposed procedures.
12 citations
TL;DR: In this article, a method for approximating dynamic nonlinear systems using parallel cascades of alternating dynamic linear and static nonlinear elements is proposed, which cannot be well fit using the first few terms of a Volterra series.
12 citations
TL;DR: In this paper, a method for obtaining a parametric NARMAX (Nonlinear Auto-Regressive Moving-Average with exogenous input) model from Volterra kernels estimated by use of input-output data is presented.
12 citations
TL;DR: The frequency distortion for the nonlinear phase-locked loop (PLL) is derived analytically using a Volterra-series approximation and comparisons are drawn between the two types of PLL with regard to the amount of distortion observed.
Abstract: In this paper, the frequency distortion for the nonlinear phase-locked loop (PLL) is derived analytically using a Volterra-series approximation. Both first- and second-order filters are considered in the PLL architecture. Theoretical results are then compared to those obtained via simulation. Comparisons are drawn between the two types of PLL with regard to the amount of distortion observed. Convergence of the Volterra-series solution is also discussed with regard to the system parameters.
12 citations