International audienceIn this paper, we propose a new tensor-based approach to identify the structure of a block-oriented nonlinear system (Hammerstein, Wiener, and Wiener-Hammerstein systems). The proposed method makes use of one time-domain Volterra kernel of an arbitrary order higher than two, which can be viewed as a tensor. We develop a tensor analysis for carrying out the identification of the structure of block-oriented nonlinear systems. The performance of the proposed identification scheme is illustrated by means of some simulation results
Abstract: In the note several algorithms for nonlinear system identification are presented. The clas...
This work aims to establish a relationship between the Polynomial NonLinear State Space (PNLSS) mode...
Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlin...
International audienceIn this paper, we propose a new tensor-based approach to identify the structur...
International audienceIn this paper, we propose tensor-based methods for identifying nonlinear Wiene...
This thesis deals with the identification of block-oriented nonlinear systems. Block-oriented nonlin...
International audienceIn this letter, we first present explicit relations between block-oriented non...
Paper describes non-linear structure identification with application to Wiener-Hammerstein systems
Wiener-Hammerstein systems consist of a series connection including a nonlinear static element sandw...
International audienceIn this paper, we consider the problem of identification of nonlinear communic...
In nonlinear system identification, the system is often represented as a series of blocks linked tog...
In this paper, we consider the problem of identification of fifth-order Wiener and Hammerstein nonli...
International audienceIn this paper, we consider the problem of identification of fifth-order Wiener...
Hammerstein systems form a class of block-oriented nonlinear models, where a static nonlinearity pre...
Nonlinear parametric system identification is the estimation of nonlinear models of dynamical system...
Abstract: In the note several algorithms for nonlinear system identification are presented. The clas...
This work aims to establish a relationship between the Polynomial NonLinear State Space (PNLSS) mode...
Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlin...
International audienceIn this paper, we propose a new tensor-based approach to identify the structur...
International audienceIn this paper, we propose tensor-based methods for identifying nonlinear Wiene...
This thesis deals with the identification of block-oriented nonlinear systems. Block-oriented nonlin...
International audienceIn this letter, we first present explicit relations between block-oriented non...
Paper describes non-linear structure identification with application to Wiener-Hammerstein systems
Wiener-Hammerstein systems consist of a series connection including a nonlinear static element sandw...
International audienceIn this paper, we consider the problem of identification of nonlinear communic...
In nonlinear system identification, the system is often represented as a series of blocks linked tog...
In this paper, we consider the problem of identification of fifth-order Wiener and Hammerstein nonli...
International audienceIn this paper, we consider the problem of identification of fifth-order Wiener...
Hammerstein systems form a class of block-oriented nonlinear models, where a static nonlinearity pre...
Nonlinear parametric system identification is the estimation of nonlinear models of dynamical system...
Abstract: In the note several algorithms for nonlinear system identification are presented. The clas...
This work aims to establish a relationship between the Polynomial NonLinear State Space (PNLSS) mode...
Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlin...