Journal ArticleAbstract-Convergence analysis of stochastic gradient adaptive filters using the sign algorithm is presented in this paper. The methods of analysis currently available in literature assume that the input signals to the filter are white. This restriction is removed for Gaussian signals in our analysis. Expressions for the second moment of the coefficient vector and the steady-state error power are also derived. Simulation results are presented, and the theoretical and empirical curves show a very good match
Bu makalede, adaptif filtre parametrelerinin iteratif olarak ayarlanmasında kullanmak için önerilen ...
In this work, the convergence and tracking behavior of the ε-normalized sign regressor least mean fo...
Abstract—Due to the inherent physical characteristics of systems under investigation, non-negativity...
Journal ArticleAdaptive filters equipped with the sign algorithm are attractive in many applications...
Journal ArticleThis paper presents two adaptive step-size gradient adaptive filters. The step sizes ...
Journal ArticleAbstract-This paper presents a tracking analysis of the adaptive filters equipped wit...
Journal ArticleAbstract-This paper presents an adaptive step-size gradient adaptive filter. The step...
We consider the convergence analysis of the sign algorithm for adaptive filtering when the input pro...
Journal ArticleAbstract-This paper presents a theoretical analysis of the stochastic gradient adapti...
AbstractThe adaptive stochastic filtering problem for Gaussian processes is considered. The self-tun...
This paper studies the mean and mean square convergence behaviors of the normalized least mean squar...
Abstract—Mean squared error (MSE) has been the dominant criterion in adaptive filter theory. A major...
In equalization and deconvolution tasks, the correlated nature of the input signal slows the converg...
This work is devoted to analyzing adaptive filtering algorithms with the use of sign-regressor for r...
In equalization and deconvolution tasks, the correlated nature of the input signal slows the converg...
Bu makalede, adaptif filtre parametrelerinin iteratif olarak ayarlanmasında kullanmak için önerilen ...
In this work, the convergence and tracking behavior of the ε-normalized sign regressor least mean fo...
Abstract—Due to the inherent physical characteristics of systems under investigation, non-negativity...
Journal ArticleAdaptive filters equipped with the sign algorithm are attractive in many applications...
Journal ArticleThis paper presents two adaptive step-size gradient adaptive filters. The step sizes ...
Journal ArticleAbstract-This paper presents a tracking analysis of the adaptive filters equipped wit...
Journal ArticleAbstract-This paper presents an adaptive step-size gradient adaptive filter. The step...
We consider the convergence analysis of the sign algorithm for adaptive filtering when the input pro...
Journal ArticleAbstract-This paper presents a theoretical analysis of the stochastic gradient adapti...
AbstractThe adaptive stochastic filtering problem for Gaussian processes is considered. The self-tun...
This paper studies the mean and mean square convergence behaviors of the normalized least mean squar...
Abstract—Mean squared error (MSE) has been the dominant criterion in adaptive filter theory. A major...
In equalization and deconvolution tasks, the correlated nature of the input signal slows the converg...
This work is devoted to analyzing adaptive filtering algorithms with the use of sign-regressor for r...
In equalization and deconvolution tasks, the correlated nature of the input signal slows the converg...
Bu makalede, adaptif filtre parametrelerinin iteratif olarak ayarlanmasında kullanmak için önerilen ...
In this work, the convergence and tracking behavior of the ε-normalized sign regressor least mean fo...
Abstract—Due to the inherent physical characteristics of systems under investigation, non-negativity...