Results 261 to 270 of about 10,846,082 (297)

Modeling and Recovery of Graph Signals and Difference-Based Signals

2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2019
In this paper, we consider the problem of representing and recovering graph signals with a nonlinear measurement model. We propose a two-stage graph signal processing (GSP) framework. First, a GSP representation is obtained by finding the graph filter that best approximates the known measurement function.
Ariel Kroizer, Yonina C. Eldar, Tirza Routtenberg   +2 more
openaire   +2 more sources

Learned-SBL: A Deep Learning Architecture for Sparse Signal Recovery

arXiv.org, 2019
In this paper, we present a computationally efficient sparse signal recovery scheme using Deep Neural Networks (DNN). The architecture of the introduced neural network is inspired from sparse Bayesian learning (SBL) and named as Learned-SBL (L-SBL).
R. J. Peter, C. Murthy
semanticscholar   +1 more source

Sparse Signal Recovery With Minimization of 1-Norm Minus 2-Norm

IEEE Transactions on Vehicular Technology, 2019
The key aim of compressed sensing is to stably recover a $K$-sparse signals ${\boldsymbol{x}}$ from a linear model ${\boldsymbol{y}}=\boldsymbol{A}{\boldsymbol{x}}+\boldsymbol{v}$, where $\boldsymbol{v}$ is a noise vector.
Jin-Ming Wen, Jian Weng, Chao Tong, Chao Ren, Zheng-Chun Zhou   +4 more
semanticscholar   +1 more source

Sublinear Recovery of Sparse Wavelet Signals

Data Compression Conference (dcc 2008), 2008
There are two main classes of decoding algorithms for "compressed sensing," those which run in time polynomial in the signal length and those which use sublinear resources. Most of the sublinear algorithms focus on signals which are compressible in either the Euclidean domain or the Fourier domain.
Ray Maleh, Anna C. Gilbert
openaire   +2 more sources

Signal recovery based on optoelectronic reservoir computing for high speed optical fiber communication system

, 2021
Shuai Wang, N. Fang, Lu-Tang Wang
semanticscholar   +1 more source

Signal recovery with convex constrained nonlinear monotone equations through conjugate gradient hybrid approach

Mathematics and Computers in Simulation, 2021
A. Halilu, Arunava Majumder, M. Waziri, K. Ahmed   +3 more
semanticscholar   +1 more source

Signal recovery methods

Physics Bulletin, 1973
Suppose that one were given the task of measuring the magnetism of a rock sample in the presence of the unavoidable and much larger magnetic field of the earth, or of measuring a weak infrared signal in a warm laboratory. In both cases the signal of interest would be obscured by a large background signal which will be referred to as 'interference' and ...
openaire   +1 more source

Signal Recovery by Proximal Forward-Backward Splitting

Multiscale Modeling & simulation, 2005
P. Combettes, Valérie R. Wajs
semanticscholar   +1 more source

Cancer Risk Among World Trade Center Rescue and Recovery Workers: A Review

Ca-A Cancer Journal for Clinicians, 2022
Andrew C Todd, Charles B. Hall, Paolo Boffetta   +2 more
exaly  

Planning for Post-Pandemic Cancer Care Delivery: Recovery or Opportunity for Redesign?

Ca-A Cancer Journal for Clinicians, 2021
Kathryn A Gold, Hope Rugo, Pelin Çınar
exaly