32 citations · 57 across the 14 of their papers we have counts for
16 papers
A Two Stage Generalized Block Orthogonal Matching Pursuit (TSGBOMP) Algorithm
Samrat Mukhopadhyay, Mrityunjoy Chakraborty
Recovery of an unknown sparse signal from a few of its projections is the key objective of compressed sensing. Often one comes across signals that are not ordinarily sparse but are…
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…
Deterministic and Randomized Diffusion based Iterative Generalized Hard Thresholding (DiFIGHT) for Distributed Sparse Signal Recovery
Samrat Mukhopadhyay, Mrityunjoy Chakraborty
In this paper we propose a distributed iterated hard thresholding algorithm termed DiFIGHT over a network that is built on the diffusion mechanism and also propose a modification o…
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…
Signal Recovery in Uncorrelated and Correlated Dictionaries Using Orthogonal Least Squares
Samrat Mukhopadhyay, Prateek Vashishtha and, Mrityunjoy Chakraborty
Though the method of least squares has been used for a long time in solving signal processing problems, in the recent field of sparse recovery from compressed measurements, this me…
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…
A Modified Multiple OLS (mOLS) Algorithm for Signal Recovery in Compressive Sensing
Samrat Mukhopadhyay, Siddhartha Satpathi, Mrityunjoy Chakraborty
Orthogonal least square (OLS) is an important sparse signal recovery algorithm for compressive sensing, which enjoys superior probability of success over other well-known recovery…
Distributed Multi-task APA over Adaptive Networks Based on Partial Diffusion
Vinay Chakravarthi Gogineni, Mrityunjoy Chakraborty
Distributed multi-task adaptive strategies are useful to estimate multiple parameter vectors simultaneously in a collaborative manner. The existed distributed multi-task strategies…
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…
Diffusion Adaptation Over Clustered Multitask Networks Based on the Affine Projection Algorithm
Vinay Chakravarthi Gogineni, Mrityunjoy Chakraborty
Distributed adaptive networks achieve better estimation performance by exploiting temporal and as well spatial diversity while consuming few resources. Recent works have studied th…
Sparse Distributed Learning via Heterogeneous Diffusion Adaptive Networks
Bijit Kumar Das, Mrityunjoy Chakraborty, Jerónimo Arenas-García
In-network distributed estimation of sparse parameter vectors via diffusion LMS strategies has been studied and investigated in recent years. In all the existing works, some convex…
On the Number of Iterations for Convergence of CoSaMP and Subspace Pursuit Algorithms
Siddhartha Satpathi, Mrityunjoy Chakraborty
In compressive sensing, one important parameter that characterizes the various greedy recovery algorithms is the iteration bound which provides the maximum number of iterations by…
Improved Bounds on RIP for Generalized Orthogonal Matching Pursuit
Siddhartha Satpathi, Rajib Lochan Das, Mrityunjoy Chakraborty
Generalized Orthogonal Matching Pursuit (gOMP) is a natural extension of OMP algorithm where unlike OMP, it may select atoms in each iteration. In this paper, we demons…
Fast and Accurate Frequency Estimation Using Sliding DFT
Anit Kumar Sahu, Mrityunjoy Chakraborty
Frequency Estimation of a complex exponential is a problem relevant to a large number of fields. In this paper a computationally efficient and accurate frequency estimator is prese…