3 citations · 5 across the 3 of their papers we have counts for
6 papers
Modified Hard Thresholding Pursuit with Regularization Assisted Support Identification
Samrat Mukhopadhyay, Mrityunjoy Chakraborty
Hard thresholding pursuit (HTP) is a recently proposed iterative sparse recovery algorithm which is a result of combination of a support selection step from iterated hard threshold…
Convergence Analysis of l0-RLS Adaptive Filter
B. K. Das, S. Mukhopadhyay, M. Chakraborty
This paper presents first and second order convergence analysis of the sparsity aware l0-RLS adaptive filter. The theorems 1 and 2 state the steady state value of mean and mean squ…
Adaptive Combination of l0 LMS Adaptive Filters for Sparse System Identification in Fluctuating Noise Power
Bijit Kumar Das, Mrityunjoy Chakraborty
Recently, the l0-least mean square (l0-LMS) algorithm has been proposed to identify sparse linear systems by employing a sparsity-promoting continuous function as an approximation…
Performance Analysis of the Gradient Comparator LMS Algorithm
Bijit Kumar Das, Mrityunjoy Chakraborty
The sparsity-aware zero attractor least mean square (ZA-LMS) algorithm manifests much lower misadjustment in strongly sparse environment than its sparsity-agnostic counterpart, the…
Performance Analysis of Norm Constrained Recursive Least Squares Algorithm
Samrat Mukhopadhyay, Bijit Kumar Das, Mrityunjoy Chakraborty
Performance analysis of norm constrained Recursive least Squares (RLS) algorithm is attempted in this paper. Though the performance pretty attractive compared to its various…
Zero Attracting PNLMS Algorithm and Its Convergence in Mean
Rajib Lochan Das, Mrityunjoy Chackraborty
The proportionate normalized least mean square (PNLMS) algorithm and its variants are by far the most popular adaptive filters that are used to identify sparse systems. The converg…