Volterra series (VS) representation is a powerful mathematical model for nonlinear circuits. However, the difficulties in determining higher order Volterra kernels limited its broader applications. In this paper, a systematic approach that enables a convenient extraction of Volterra kernels from X-parameters is presented. A concise and general representation of the output response due to arbitrary number of input tones is given. The relationship between Volterra kernels and X-parameters is explicitly formulated. An efficient frequency sweep scheme and an output frequency indexing scheme are provided. The least square linear regression method is employed to separate different orders of Volterra kernels at the same frequency, which leads to t...
Volterra series expansions are widely used in analysing and solving the problems of nonlinear dynami...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an ele...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an ele...
Volterra series representation is a powerful mathematical model for nonlinear devices. However, the ...
The Volterra series model is a direct generalisation of the linear convolution integral and is capab...
Volterra series approximate a broad range of nonlinear systems. Their identification is challenging ...
This paper describes a modeling approach for nonlinear dynamic systems based on a modified Volterra ...
Cette thèse porte sur l’identification de systèmes non linéaires représentables en séries de Volterr...
Abstract: Volterra series (VS) are widely used in non-linear dynamical system identification. Much p...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an elec...
Cataloged from PDF version of article.A new method is proposed for the transient analysis of circui...
Volterra series expansions are widely used in analysing and solving the problems of nonlinear dynami...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an ele...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an ele...
Volterra series representation is a powerful mathematical model for nonlinear devices. However, the ...
The Volterra series model is a direct generalisation of the linear convolution integral and is capab...
Volterra series approximate a broad range of nonlinear systems. Their identification is challenging ...
This paper describes a modeling approach for nonlinear dynamic systems based on a modified Volterra ...
Cette thèse porte sur l’identification de systèmes non linéaires représentables en séries de Volterr...
Abstract: Volterra series (VS) are widely used in non-linear dynamical system identification. Much p...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
The Volterra approach to the modeling of nonlinear systems has been employed for a long time thanks ...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an elec...
Cataloged from PDF version of article.A new method is proposed for the transient analysis of circui...
Volterra series expansions are widely used in analysing and solving the problems of nonlinear dynami...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an ele...
We have developed a Neural Network model able to reproduce some nonlinear characteristics of an ele...