This paper presents a new adaptive technique for the identification of a linear system driven by white non-Gaussian noise. The system can be a non-minimum phase system. The adaptive identification technique is a least mean-square (LMS) type algorithm and it is obtained by using the higher order correlations of the system output. © 1991 IEE
The main theme of this thesis is black-box mathematical modeling of discrete-time, finite-dimensiona...
This paper considers the problem of identifying continuous-time linear time-invariant systems in fre...
In this paper, we propose a new adaptive filtering algorithm for system identification. The algorith...
In this paper, we develop the adaptive algorithm for system identification where the model is sparse...
This paper presents the experimental development of software and hardware configuration to implement...
Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advant...
In this paper a modified identification algorithm for linear systems with noisy input-output data is...
System characteristic identification using normal operating signals and additive test signals is dis...
System characteristic identification using normal operating signals and additive test signals is dis...
This paper considers the problem of adaptive identification of IIR systems when the system output is...
When the input-output data of a system are given and the mathematical model of this system is desire...
This thesis deals with two related subjects: adaptive algorithms in signal processing and system ide...
A real time computational method is presented for the identification of linear discrete dynamic syst...
International audienceDynamic system modeling plays a crucial role in the development of techniques ...
This paper considers the on-line identification of a non-linear system in terms of a Hammerstein mod...
The main theme of this thesis is black-box mathematical modeling of discrete-time, finite-dimensiona...
This paper considers the problem of identifying continuous-time linear time-invariant systems in fre...
In this paper, we propose a new adaptive filtering algorithm for system identification. The algorith...
In this paper, we develop the adaptive algorithm for system identification where the model is sparse...
This paper presents the experimental development of software and hardware configuration to implement...
Standard least mean square/fourth (LMS/F) is a classical adaptive algorithm that combined the advant...
In this paper a modified identification algorithm for linear systems with noisy input-output data is...
System characteristic identification using normal operating signals and additive test signals is dis...
System characteristic identification using normal operating signals and additive test signals is dis...
This paper considers the problem of adaptive identification of IIR systems when the system output is...
When the input-output data of a system are given and the mathematical model of this system is desire...
This thesis deals with two related subjects: adaptive algorithms in signal processing and system ide...
A real time computational method is presented for the identification of linear discrete dynamic syst...
International audienceDynamic system modeling plays a crucial role in the development of techniques ...
This paper considers the on-line identification of a non-linear system in terms of a Hammerstein mod...
The main theme of this thesis is black-box mathematical modeling of discrete-time, finite-dimensiona...
This paper considers the problem of identifying continuous-time linear time-invariant systems in fre...
In this paper, we propose a new adaptive filtering algorithm for system identification. The algorith...