This letter describes how to set up the step size of the affine projection algorithm (APA) based on mean-square deviation analysis. The analysis considers the cross-correlation between the current weight error vector and the prior measurement noises associated with the reused inputs vectors for better prediction of the learning behavior of the APA. With the predetermined step size based on the analysis, the proposed approach eliminates the parameter-tuning process and the derived algorithm achieves both the fast convergence rate and the low steady-state error. Simulation results show that the proposed algorithm performs better than previous algorithms.X111719sciescopu
In this paper, we present a theoretical convergence analysis of the affine projection algorithm (APA...
DoctorThis dissertation proposes the various methods to improve the performance of a family of affin...
This paper introduces a new variable step-size APA with decorrelation of AR input process is based o...
DoctorThis dissertation introduces mean-square analysis of affine projection algorithm(APA).The prop...
This paper presents an improved mean-square deviation (MSD) analysis of the standard affine projecti...
Proposed is a variable step-size affine projection sign algorithm (APSA) based on the minimisation o...
This paper presents a regularized modification to the weighted variable step-size affine projection ...
In this paper, we propose a variable matrix-type step-size affine projection algorithm (APA) with or...
We present a novel affine projection algorithm (APA) which dynamically selects input vectors in orde...
This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (...
This letter proposes a variable step-size (VSS) affine projection algorithm (APA) associated with a ...
This paper presents a mean-square deviation (MSD) analysis of the periodic affine projection algorit...
An algorithm that introduces a novel scheme for the combination of the two adaptation terms of the a...
This letter proposes two new variable step-size algorithms for normalized least mean square and affi...
This paper introduces an optimal variable step-size affine projection algorithm for the modified fil...
In this paper, we present a theoretical convergence analysis of the affine projection algorithm (APA...
DoctorThis dissertation proposes the various methods to improve the performance of a family of affin...
This paper introduces a new variable step-size APA with decorrelation of AR input process is based o...
DoctorThis dissertation introduces mean-square analysis of affine projection algorithm(APA).The prop...
This paper presents an improved mean-square deviation (MSD) analysis of the standard affine projecti...
Proposed is a variable step-size affine projection sign algorithm (APSA) based on the minimisation o...
This paper presents a regularized modification to the weighted variable step-size affine projection ...
In this paper, we propose a variable matrix-type step-size affine projection algorithm (APA) with or...
We present a novel affine projection algorithm (APA) which dynamically selects input vectors in orde...
This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (...
This letter proposes a variable step-size (VSS) affine projection algorithm (APA) associated with a ...
This paper presents a mean-square deviation (MSD) analysis of the periodic affine projection algorit...
An algorithm that introduces a novel scheme for the combination of the two adaptation terms of the a...
This letter proposes two new variable step-size algorithms for normalized least mean square and affi...
This paper introduces an optimal variable step-size affine projection algorithm for the modified fil...
In this paper, we present a theoretical convergence analysis of the affine projection algorithm (APA...
DoctorThis dissertation proposes the various methods to improve the performance of a family of affin...
This paper introduces a new variable step-size APA with decorrelation of AR input process is based o...