Results 271 to 280 of about 46,224 (313)

Optical CDMA Detection by Orthogonal Matching Pursuit

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
In this paper, we present a novel optical CDMA multi-user detector employing the orthogonal matching pursuit algorithm. The proposed system is compared with most of the receiver structures in the literature. It is shown by simulation results that the proposed detection architecture is a very promising candidate with its low computational complexity ...
T. Kurt, G. Karabulut, A. Yongacoglu
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Dispersion curve recovery with orthogonal matching pursuit

The Journal of the Acoustical Society of America, 2014
Dispersion curves characterize many propagation mediums. When known, many methods use these curves to analyze waves. Yet, in many scenarios, their exact values are unknown due to material and environmental uncertainty. This paper presents a fast implementation of sparse wavenumber analysis, a method for recovering dispersion curves from data.
Joel B, Harley, José M F, Moura
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Sorted Random Matrix for Orthogonal Matching Pursuit

2010 International Conference on Digital Image Computing: Techniques and Applications, 2010
Orthogonal Matching Pursuit (OMP) algorithm is widely applied to compressive sensing (CS) image signal recovery because of its low computation complexity and its ease of implementation. However, OMP usually needs more measurements than some other recovery algorithms in order to achieve equal-quality reconstructions. This article firstly illustrates the
Zhenglin Wang, Ivan Lee
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Orthogonal matching pursuit for VHR image reconstruction

2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
Reconstructing missing data in very high resolution (VHR) multispectral images represents a complex image processing challenge. In this paper, we propose a new method for the reconstruction of areas obscured by clouds. It is based on compressive sensing (CS) theory, which allows to find sparse signal representations in underdetermined linear equation ...
Lorenzi, Luca, Melgani, Farid, G. Mercier   +2 more
openaire   +1 more source

Orthogonal Matching Pursuit Algorithm Via Improved Matching Criterion

Proceedings of the 2nd International Conference on Digital Signal Processing, 2018
Better support set Selected is the key step in Compressed Sensing to improve the reconstruction effect. The inner product matching criterion adopted in orthogonal matching pursuit algorithm fails to fully consider the correlation between the residuals and the atoms, which leads to greater error in the reconstruction process.
Jianhong Xiang, Huihui Yue, Xiangjun Yin
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Reduced Look Ahead Orthogonal Matching Pursuit

2014 Twentieth National Conference on Communications (NCC), 2014
Compressed Sensing (CS) is an elegant technique to acquire signals and reconstruct them efficiently by solving a system of under-determined linear equations. The excitement in this field stems from the fact that we can sample at a rate way below the Nyquist rate and still reconstruct the signal provided some conditions are met.
Prateek Basavapur Swamy, Sooraj K. Ambat, Saikat Chatterjee, K.V.S. Hari   +3 more
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Normalized regularized orthogonal matching pursuit algorithm

2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2015
The idea of regularized orthogonal matching pursuit(ROMP) algorithm is to select multiple orthogonal column vectors at each iteration. Once chosen by mistake, the vectors can't be deleted from the support set, so that the algorithm can't be applied to signals with large sparity.
Zhang Tao, Bai Zhengyao, Yang Lu
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Orthogonal Matching Pursuit on Faulty Circuits

IEEE Transactions on Communications, 2015
With the wide recognition that modern nanoscale devices will be error-prone, characterization of reliability of information processing systems built out of unreliable components has become an important topic. In this paper, we analyze the performance of orthogonal matching pursuit (OMP), a popular sparse recovery algorithm, running on faulty circuits ...
Yao Li, Yuejie Chi, Chu-Hsiang Huang, Lara Dolecek   +3 more
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Two-dimensional Newtonized orthogonal matching pursuit compressive beamforming

The Journal of the Acoustical Society of America, 2020
Conventional compressive beamforming assumes that the acoustic sources fall on the discretized grid points. The performance degrades when the acoustic source lies off the discretized grid point, that is, when the basis mismatch occurs. This paper proposes a two-dimensional Newtonized orthogonal matching pursuit compressive beamforming, including single
Yongxin Yang, Zhigang Chu, Yang Yang, Shijia Yin   +3 more
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A fast orthogonal matching pursuit algorithm

Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), 2002
The problem of optimal approximation of members of a vector space by a linear combination of members of a large overcomplete library of vectors is of importance in many areas including image and video coding, image analysis, control theory, and statistics. Finding the optimal solution in the general case is mathematically intractable. Matching pursuit,
M. Gharavi-Alkhansari, T.S. Huang
openaire   +1 more source