The expectation of the square of the reflection coefficient in small samples of white noise is derived. This variance of the reflection coefficient in white noise is a key factor in the statistics of the estimation of autoregressive (AR) models in small samples. Approximations of this expectation are constructed that are more accurate than the known first-order Taylor approximation. These better approximations are needed, because in some applications (radar applications, for example) the number of observations is small (say 63 observations) and asymptotic descriptions do not cover the estimates
The INteger-valued AutoRegressive (INAR) processes were introduced in the lite-rature by Al-Osh and ...
Autoregressive spectral analysis depends on the method used for estimating the autoregressive parame...
A simple algorithm is developed for unbiased parameter identification of autoregressive (AR) signals...
The expectation of the square of the reflection coefficient in small samples of white noise is deriv...
In this paper we will give the expectation of (the square of) the reflection coefficient, residual v...
The Yule-Walker (YW) method for autoregressive (AR) estimation uses lagged-product (LP) autocorrelat...
The exact statistics of the estimated reflection coefficients for an autoregressive process are diff...
Abstract. I n a number of applications involving the processing of noisy signals, it is desirable to...
A common approach in modeling signals in many engineering applications consists in adopting autoregr...
copyright(c)2004 IEICE 許諾番号:07RB0174The processing of noise-corrupted signals is a common problem in...
We consider the problem of estimating the parameters of an autoregressive process based on observati...
Abstract- Autoregressive modelling of noise data is widely used for system identification, surveilla...
International audienceTwo sets of random vectors cannot both be Gaussian if they are nonlinearly rel...
Estimating the autoregressive parameters from noisy observations has been addressed by various autho...
Recently a method of estimating the parameters of an AR(p) random process based on measurements corr...
The INteger-valued AutoRegressive (INAR) processes were introduced in the lite-rature by Al-Osh and ...
Autoregressive spectral analysis depends on the method used for estimating the autoregressive parame...
A simple algorithm is developed for unbiased parameter identification of autoregressive (AR) signals...
The expectation of the square of the reflection coefficient in small samples of white noise is deriv...
In this paper we will give the expectation of (the square of) the reflection coefficient, residual v...
The Yule-Walker (YW) method for autoregressive (AR) estimation uses lagged-product (LP) autocorrelat...
The exact statistics of the estimated reflection coefficients for an autoregressive process are diff...
Abstract. I n a number of applications involving the processing of noisy signals, it is desirable to...
A common approach in modeling signals in many engineering applications consists in adopting autoregr...
copyright(c)2004 IEICE 許諾番号:07RB0174The processing of noise-corrupted signals is a common problem in...
We consider the problem of estimating the parameters of an autoregressive process based on observati...
Abstract- Autoregressive modelling of noise data is widely used for system identification, surveilla...
International audienceTwo sets of random vectors cannot both be Gaussian if they are nonlinearly rel...
Estimating the autoregressive parameters from noisy observations has been addressed by various autho...
Recently a method of estimating the parameters of an AR(p) random process based on measurements corr...
The INteger-valued AutoRegressive (INAR) processes were introduced in the lite-rature by Al-Osh and ...
Autoregressive spectral analysis depends on the method used for estimating the autoregressive parame...
A simple algorithm is developed for unbiased parameter identification of autoregressive (AR) signals...