Results 21 to 30 of about 322,181 (285)

Efficient sparse coding in early sensory processing: lessons from signal recovery. [PDF]

PLoS Computational Biology, 2012
Sensory representations are not only sparse, but often overcomplete: coding units significantly outnumber the input units. For models of neural coding this overcompleteness poses a computational challenge for shaping the signal processing channels as ...
András Lörincz, Zsolt Palotai, Gábor Szirtes   +2 more
doaj   +1 more source

Sparse approximations in signal and image processing [PDF]

Signal Processing, 2006
Guest editorial of the special issue on Sparse Approximations in Signal and Image ...
Gribonval, R., Nielsen, M.
openaire   +2 more sources

Sparse Recovery Algorithm for Compressed Sensing Using Smoothed l₀ Norm and Randomized Coordinate Descent

Mathematics, 2019
Compressed sensing theory is widely used in the field of fault signal diagnosis and image processing. Sparse recovery is one of the core concepts of this theory.
Dingfei Jin, Guang Yang, Zhenghui Li, Haode Liu   +3 more
doaj   +1 more source

Block-Sparse Recovery via Convex Optimization [PDF]

, 2012
Given a dictionary that consists of multiple blocks and a signal that lives in the range space of only a few blocks, we study the problem of finding a block-sparse representation of the signal, i.e., a representation that uses the minimum number of ...
Ehsan Elhamifar, Rene ́ Vidal, Senior Member, Student Member   +3 more
core   +1 more source

Cluster-Sparse Proportionate NLMS Algorithm With the Hybrid Norm Constraint

IEEE Access, 2018
In this paper, an enhanced proportionate normalized least mean square (PNLMS) algorithm with the hybrid l2,0-norm constraint is proposed for block-sparse signal processing.
Yingsong Li, Zhengxiong Jiang, Zhan Jin, Xiao Han, Jingwei Yin   +4 more
doaj   +1 more source

Imaging Method for Co-prime-sampling Space-borne SAR Based on 2D Sparse-signal Reconstruction

Leida xuebao, 2020
Co-prime-sampling space-borne Synthetic Aperture Radar (SAR) replaces the traditional uniform sampling by performing co-prime sampling in azimuth, which effectively alleviates the conflict between spatial resolution and effective swath width, while also
ZHAO Wanwan, WANG Pengbo, MEN Zhirong, LI Chunsheng   +3 more
doaj   +1 more source

Sparse Analysis Recovery via Iterative Cosupport Detection Estimation

IEEE Access, 2021
Cosparse analysis model (CAM) provides a new signal processing paradigm for recovering cosparse signals with respect to a given analysis operator from the undersampled linear measurements in the context of emerging theory of compressed sensing (CS).
Heping Song, Xiaolong Ren, Yuping Lai, Hongying Meng   +3 more
doaj   +1 more source

Weak Signal Detection Based on Combination of Sparse Representation and Singular Value Decomposition

Applied Sciences, 2022
Due to the inevitable acquisition system noise and strong background noise, it is often difficult to detect the features of weak signals. To solve this problem, sparse representation can effectively extract useful information according to the sparse ...
Huijie Ma, Shunming Li, Xianglian Li, Jiantao Lu   +3 more
doaj   +1 more source

A Review of Radar Signal Processing Based on Sparse Recovery

Leida xuebao
With the growing demand for radar target detection, Sparse Recovery (SR) technology based on the Compressive Sensing (CS) model has been widely used in radar signal processing.
Yinghui QUAN, Yaojun WU, Lining DUAN, Gang XU, Min XUE, Zhixing LIU, Mengdao XING   +6 more
doaj   +1 more source

2-D Joint Sparse Reconstruction and Micro-Motion Parameter Estimation for Ballistic Target Based on Compressive Sensing

Sensors, 2020
The sparse frequency band (SFB) signal presents a serious challenge to traditional wideband micro-motion curve extraction algorithms. This paper proposes a novel two-dimension (2-D) joint sparse reconstruction and micro-motion parameter estimation (2D ...
Jiaqi Wei, Shuai Shao, Lei Zhang, Hongwei Liu   +3 more
doaj   +1 more source