International audienceThis letter is concerned with the parameter estimation of linear and nonlinear subsystems of parallel-cascade Wiener systems (PCWS). We first present the relationship between a PCWS and its associated Volterra model. We show that the coefficients of the linear subsystems can be obtained using a joint diagonalization of the third-order Volterra kernel slices. Then, the coefficients of the nonlinear subsystems are estimated using the least square algorithm. The proposed parameter estimation method is illustrated by means of simulation result
International audienceDiscrete-time Volterra models are widely used in various application areas. Th...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
International audienceThis letter is concerned with the parameter estimation of linear and nonlinear...
International audienceIn this letter, we first present explicit relations between block-oriented non...
International audienceIn this paper, we consider the problem of identification of fifth-order Wiener...
In this paper, we consider the problem of identification of fifth-order Wiener and Hammerstein nonli...
\u3cp\u3eThis paper proposes a parametric identification method for parallel Wiener systems, startin...
reconstruction. The nonlinear system identification based on the Volterra model is applicable only f...
3Multivariance identification methods exploit input signals with multiple variances for estimating t...
Multivariance identification methods exploit input signals with multiple variances for estimating th...
13th IFAC Symposium on System Identification, SYSID 2003 -- 27 August 2003 through 29 August 2003 --...
Volterra and Wiener series are perhaps the best understood nonlinear system representations in signa...
We present a technique for kernel-based identification of Wiener systems. We model the impulse respo...
A Wiener model is a fairly simple, well known, and often used nonlinearblock-oriented black-box mode...
International audienceDiscrete-time Volterra models are widely used in various application areas. Th...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
International audienceThis letter is concerned with the parameter estimation of linear and nonlinear...
International audienceIn this letter, we first present explicit relations between block-oriented non...
International audienceIn this paper, we consider the problem of identification of fifth-order Wiener...
In this paper, we consider the problem of identification of fifth-order Wiener and Hammerstein nonli...
\u3cp\u3eThis paper proposes a parametric identification method for parallel Wiener systems, startin...
reconstruction. The nonlinear system identification based on the Volterra model is applicable only f...
3Multivariance identification methods exploit input signals with multiple variances for estimating t...
Multivariance identification methods exploit input signals with multiple variances for estimating th...
13th IFAC Symposium on System Identification, SYSID 2003 -- 27 August 2003 through 29 August 2003 --...
Volterra and Wiener series are perhaps the best understood nonlinear system representations in signa...
We present a technique for kernel-based identification of Wiener systems. We model the impulse respo...
A Wiener model is a fairly simple, well known, and often used nonlinearblock-oriented black-box mode...
International audienceDiscrete-time Volterra models are widely used in various application areas. Th...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
The aim of the given paper is the development of an approach for parametric identification of Wiener...