This paper presents a new algorithm that can solve the problem of selecting appropriate update step size in the LMS algorithm. The proposed algorithm, called a Complementary Pail LMS (CP-LIMS) algorithm, consists of two adaptive filters with different update step sizes operating in parallel, one filter re-initializing the other with the better coefficient estimates whenever possible. This new algorithm provides the faster convergence speed and the smaller steady-state error than those of a single filter with a fixed or variable step size.open1114sciescopu
The Normalized Least Mean Square (NLMS) algorithm is an important variant of the classical LMS algor...
Abstract—This paper presents a precise analysis of the crit-ical path of the least-mean-square (LMS)...
The complexity of an adaptive filtering algorithm is proportional to the tap length of the filter an...
[[abstract]]© 1992 Elsevier - In this paper, a two step-size LMS algorithm, called dual LMS (DLMS) a...
[[abstract]]© 1992 Institute of Electrical and Electronics Engineers - A two step-size LMS algorithm...
The LMS algorithm invented by Widrow and Hoff in 1959 is the simplest, most robust, and one of the m...
Partial updating of LMS filter coefficients is an effective method for reducing the computational lo...
A new adaptive filter algorithm has been developed that combines the benefits of the Least Mean Squa...
This paper derives an upper bound for the step size of the sequential partial update (PU) LMS adapt...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
We present a low-complexity complementary pair affine projection (CP-AP) adaptive filter which emplo...
We present analytical results, and details of implementation for a novel adaptive filter incorporati...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Shows that the NLMS (normalized least-mean-square) algorithm is a potentially faster converging algo...
The LMS adaptive algorithm has always been attractive to researchers in the field of adaptive signal...
The Normalized Least Mean Square (NLMS) algorithm is an important variant of the classical LMS algor...
Abstract—This paper presents a precise analysis of the crit-ical path of the least-mean-square (LMS)...
The complexity of an adaptive filtering algorithm is proportional to the tap length of the filter an...
[[abstract]]© 1992 Elsevier - In this paper, a two step-size LMS algorithm, called dual LMS (DLMS) a...
[[abstract]]© 1992 Institute of Electrical and Electronics Engineers - A two step-size LMS algorithm...
The LMS algorithm invented by Widrow and Hoff in 1959 is the simplest, most robust, and one of the m...
Partial updating of LMS filter coefficients is an effective method for reducing the computational lo...
A new adaptive filter algorithm has been developed that combines the benefits of the Least Mean Squa...
This paper derives an upper bound for the step size of the sequential partial update (PU) LMS adapt...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
We present a low-complexity complementary pair affine projection (CP-AP) adaptive filter which emplo...
We present analytical results, and details of implementation for a novel adaptive filter incorporati...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
Shows that the NLMS (normalized least-mean-square) algorithm is a potentially faster converging algo...
The LMS adaptive algorithm has always been attractive to researchers in the field of adaptive signal...
The Normalized Least Mean Square (NLMS) algorithm is an important variant of the classical LMS algor...
Abstract—This paper presents a precise analysis of the crit-ical path of the least-mean-square (LMS)...
The complexity of an adaptive filtering algorithm is proportional to the tap length of the filter an...