This paper is concerned with FIR filtering with noise-corrupted input-output measurements. With an analysis of the algebraic structure of the correlation matrix, it is shown that an unbiased estimate of FIR parameters can be obtained by solving a special bilinear equation. Then a bilinear equation method (BEM) is developed for solving the bilinear equation associated with the unbiased solution of the FIR filtering under the unknown ratio of the input noise variance to the output noise variance (NNR). Being different from the existing unbiased estimators, the main advantage is that the proposed method exploits much sufficiently the special structure of the correlation matrix and obtains much accurate estimation for FIR filtering in the prese...
DoctorAdaptive filters have been used in a wide variety of applications such as noise cancellation, ...
This paper is concerned with parameter estimation of autoregressive (AR) signals from noisy observat...
In this paper a modified identification algorithm for linear systems with noisy input-output data is...
In this paper the problem of finite impulse response (FIR) filtering with noisy input-output data is...
This paper describes a method for identifying FIR models in the presence of input and output noise. ...
This paper describes a method for identifying FIR models in the presence of input and output noise. ...
This paper is concerned with identifying parameters of finite impulse response (FIR) systems from no...
This paper proposes an efficient algorithm for identifying FIR models when also the input is assumed...
This paper proposes an efficient algorithm for identifying FIR models when also the input is assumed...
In this paper, by assuming that the ratio between the output noise variance and the input noise vari...
none1noA new bias-compensated least-squares method for identifying finite impulse response (FIR) mod...
This paper addresses the problem of parameter estimation of noisy input-output models, where the mea...
This paper deals with the identification of FIR models corrupted by white input noise and colored o...
This paper deals with the identification of FIR models corrupted by white input noise and colored o...
none3This paper proposes an efficient algorithm for identifying FIR models when also the input is as...
DoctorAdaptive filters have been used in a wide variety of applications such as noise cancellation, ...
This paper is concerned with parameter estimation of autoregressive (AR) signals from noisy observat...
In this paper a modified identification algorithm for linear systems with noisy input-output data is...
In this paper the problem of finite impulse response (FIR) filtering with noisy input-output data is...
This paper describes a method for identifying FIR models in the presence of input and output noise. ...
This paper describes a method for identifying FIR models in the presence of input and output noise. ...
This paper is concerned with identifying parameters of finite impulse response (FIR) systems from no...
This paper proposes an efficient algorithm for identifying FIR models when also the input is assumed...
This paper proposes an efficient algorithm for identifying FIR models when also the input is assumed...
In this paper, by assuming that the ratio between the output noise variance and the input noise vari...
none1noA new bias-compensated least-squares method for identifying finite impulse response (FIR) mod...
This paper addresses the problem of parameter estimation of noisy input-output models, where the mea...
This paper deals with the identification of FIR models corrupted by white input noise and colored o...
This paper deals with the identification of FIR models corrupted by white input noise and colored o...
none3This paper proposes an efficient algorithm for identifying FIR models when also the input is as...
DoctorAdaptive filters have been used in a wide variety of applications such as noise cancellation, ...
This paper is concerned with parameter estimation of autoregressive (AR) signals from noisy observat...
In this paper a modified identification algorithm for linear systems with noisy input-output data is...