L₁/L₂-Mode Switching Adaptive Filter Algorithm Based on Novel Mean Square Deviation Analysis

Steady-state mean-square-deviation analysis of the sign subband adaptive filter algorithm

Recently, the sign subband adaptive filter (SSAF) algorithm has obtained great attention, due to its robustness against impulsive noises and decorrelating property for correlated input signals. However, the performance of the algorithm in the steady-state is not analyzed. In this paper, we study the steady-state mean-square-deviation (MSD) behavior of the SSAF algorithm by using energy conserva...

Analysis of the Entropy-guided Switching Trimmed Mean Deviation-based Anisotropic Diffusion filter

Abstract This report describes the experimental analysis of a proposed switching filter-anisotropic diffusion hybrid for the filtering of the fixed value (salt and pepper) impulse noise (FVIN). The filter works well at both low and high noise densities though it was specifically designed for high noise density levels. The filter combines the switching mechanism of decision-based filters and the...

On Weighted Pcm and Mean Square Deviation

Mean square convergence analysis for kernel least mean square algorithm

In this paper, we study the mean square convergence of the kernel least mean square (KLMS). The fundamental energy conservation relation has been established in feature space. Starting from the energy conservation relation, we carry out the mean square convergence analysis and obtain several important theoretical results, including an upper bound on step size that guarantees the mean square con...

Unconstrained Hartley Domain Least Mean Square Adaptive Filter

Peak detection is a basic data analysis problem which isessential in a large number of applications. In applications such asimage processing, the large computational effort to locate peaks mayprohibit operation in real-time. A Hopfield neural network is proposedfor the peak detector to solve the real-time problem. Analytical expres-sions are derivedfor input separation, ...