Stochastic Gradient Matching Pursuit Algorithm Based on Sparse Estimation

Sparse Multipath Channel Estimation Using Compressive Sampling Matching Pursuit Algorithm

Wideband wireless channel is a time dispersive channel and becomes strongly frequency-selective. However, in most cases, the channel is composed of a few dominant taps and a large part of taps is approximately zero or zero. To exploit the sparsity of multi-path channel (MPC), two methods have been proposed. They are, namely, greedy algorithm and convex program. Greedy algorithm is easy to be im...

Sparse Estimation Based on a New Random Regularized Matching Pursuit Generalized Approximate Message Passing Algorithm

Yongjie Luo 1, Guan Gui 2,*, Xunchao Cong 1 and Qun Wan 1 1 Department of Electronic Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengdu 611731, China; [email protected] (X.C.); [email protected] (Q.W.) 2 College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications,...

Stochastic Information Gradient Algorithm Based on Maximum Entropy Density Estimation

Sparse channel estimation via matching pursuit with application to equalization

Channels with a sparse impulse response arise in a number of communication applications. Exploiting the sparsity of the channel, we show how an estimate of the channel may be obtained using a matching pursuit (MP) algorithm. This estimate is compared to thresholded variants of the least squares (LS) channel estimate. Among these sparse channel estimates, the MP estimate is computationally much ...

Improvement of Compressive Sampling and Matching Pursuit Algorithm Based on Double Estimation

—Compression sampling matching pursuit algorithm (CoSaMP) is widely applied to image reconstruction owing to its high precision of reconstruction, robustness, and simple operation. In this paper, we propose a new method, the CoSaMP based on double estimation, to properly overcome the shortcomings in CoSaMP for choosing too much optional atoms and imprecise choice. The concept of the maximum es...