Zobrazeno 1 - 10
of 147
pro vyhledávání: '"Tripp, A. E."'
This paper introduces a nonconvex approach for sparse signal recovery, proposing a novel model termed the $\tau_2$-model, which utilizes the squared $\ell_1/\ell_2$ norms for this purpose. Our model offers an advancement over the $\ell_0$ norm, which
Externí odkaz:
http://arxiv.org/abs/2404.00764
We develop a recursive least square (RLS) type algorithm with a minimax concave penalty (MCP) for adaptive identification of a sparse tap-weight vector that represents a communication channel. The proposed algorithm recursively yields its estimate of
Externí odkaz:
http://arxiv.org/abs/2211.03903
Despite the fact that Shannon and Weaver's Mathematical Theory of Communication was published over 70 years ago, all communication systems continue to operate at the first of three levels defined in this theory: the technical level. In this letter, w
Externí odkaz:
http://arxiv.org/abs/2210.01629
Despite being the subject of a growing body of research, non-orthogonal multiple access has failed to garner sufficient support to be included in modern standards. One of the more promising approaches to non-orthogonal multiple access is sparse code
Externí odkaz:
http://arxiv.org/abs/2208.06307
The log-sum penalty is often adopted as a replacement for the $\ell_0$ pseudo-norm in compressive sensing and low-rank optimization. The hard-thresholding operator, i.e., the proximity operator of the $\ell_0$ penalty, plays an essential role in appl
Externí odkaz:
http://arxiv.org/abs/2103.02681
Sparsity promoting functions (SPFs) are commonly used in optimization problems to find solutions which are assumed or desired to be sparse in some basis. For example, the l1-regularized variation model and the Rudin-Osher-Fatemi total variation (ROF-
Externí odkaz:
http://arxiv.org/abs/1909.05419
Motivated by the minimax concave penalty based variable selection in high-dimensional linear regression, we introduce a simple scheme to construct structured semiconvex sparsity promoting functions from convex sparsity promoting functions and their M
Externí odkaz:
http://arxiv.org/abs/1809.06777
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Publikováno v:
In Journal of Forensic and Legal Medicine January 2020 69
Akademický článek
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