Tracking analysis of normalized adaptive algorithms is carried out in the presence of two sources of nonstationarities: carrier frequency offset between transmitter and receiver; random variations in the environment. A unified approach is carried out using a mixed-norm-type error nonlinearity. Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset
DoctorAdaptive filters that self-adjust their transfer functions according to optimization algorithm...
In this work, expressions are derived for the steady-state excess-mean-square error (EMSE) of the ε-...
This paper discusses the convergence and tracking behaviour of LMS-type algorithms in a certain type...
Tracking analysis of normalized adaptive algorithms is carried out in the presence of two sources of...
Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presenc...
Abstract: Problem statement: This study introduced a variable step-size Least Mean-Square (LMS) algo...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
DoctorThis thesis proposes the mean-square-deviation (MSD) analysis of the normalized subband adapti...
This paper studies the tracking performance of adaptive filters operating in the presence of two sou...
In this work, expressions for the tracking excess-mean-square error (EMSE) and optimum step-size of ...
: In this paper, an analysis of the tracking performance of several adaptive algorithms is carried o...
The Normalized Least Mean Square (NLMS) algorithm is an important variant of the classical LMS algor...
In this paper, an analysis of the tracking performance of several adaptive algorithms is carried out...
The task of adaptive estimation in the presence of random and highly nonlinear environment such as w...
Journal ArticleThis paper presents a tracking analysis of the adaptive filters equipped with the sig...
DoctorAdaptive filters that self-adjust their transfer functions according to optimization algorithm...
In this work, expressions are derived for the steady-state excess-mean-square error (EMSE) of the ε-...
This paper discusses the convergence and tracking behaviour of LMS-type algorithms in a certain type...
Tracking analysis of normalized adaptive algorithms is carried out in the presence of two sources of...
Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presenc...
Abstract: Problem statement: This study introduced a variable step-size Least Mean-Square (LMS) algo...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
DoctorThis thesis proposes the mean-square-deviation (MSD) analysis of the normalized subband adapti...
This paper studies the tracking performance of adaptive filters operating in the presence of two sou...
In this work, expressions for the tracking excess-mean-square error (EMSE) and optimum step-size of ...
: In this paper, an analysis of the tracking performance of several adaptive algorithms is carried o...
The Normalized Least Mean Square (NLMS) algorithm is an important variant of the classical LMS algor...
In this paper, an analysis of the tracking performance of several adaptive algorithms is carried out...
The task of adaptive estimation in the presence of random and highly nonlinear environment such as w...
Journal ArticleThis paper presents a tracking analysis of the adaptive filters equipped with the sig...
DoctorAdaptive filters that self-adjust their transfer functions according to optimization algorithm...
In this work, expressions are derived for the steady-state excess-mean-square error (EMSE) of the ε-...
This paper discusses the convergence and tracking behaviour of LMS-type algorithms in a certain type...