Results 11 to 20 of about 3,086,556 (345)
Universal compressed sensing [PDF]
2016 IEEE International Symposium on Information Theory (ISIT), 2016 In this paper, the problem of developing universal algorithms for compressed sensing of stochastic processes is studied. First, R nyi's notion of information dimension (ID) is generalized to analog stationary processes. This provides a measure of complexity for such processes and is connected to the number of measurements required for their accurate ...
Jalali, Shirin, Poor, H. Vincent
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"Compressed" Compressed Sensing
, 2010 The field of compressed sensing has shown that a sparse but otherwise arbitrary vector can be recovered exactly from a small number of randomly constructed linear projections (or samples). The question addressed in this paper is whether an even smaller number of samples is sufficient when there exists prior knowledge about the distribution of the ...
Reeves, Galen, Gastpar, Michael
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From compression to compressed sensing [PDF]
2013 IEEE International Symposium on Information Theory, 2013 Can compression algorithms be employed for recovering signals from their underdetermined set of linear measurements? Addressing this question is the first step towards applying compression algorithms for compressed sensing (CS). In this paper, we consider a family of compression algorithms $\mathcal{C}_r$, parametrized by rate $r$, for a compact class ...
Jalali, Shirin, Maleki, Arian
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Compressed wavefront sensing [PDF]
Optics Letters, 2014 We report on an algorithm for fast wavefront sensing that incorporates sparse representation for the first time in practice. The partial derivatives of optical wavefronts were sampled sparsely with a Shack-Hartman wavefront sensor (SHWFS) by randomly subsampling the original SHWFS data to as little as 5%.
James, Polans +3 more
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Fully Learnable Model for Task-Driven Image Compressed Sensing
Sensors, 2021 This study primarily investigates image sensing at low sampling rates with convolutional neural networks (CNN) for specific applications. To improve the image acquisition efficiency in energy-limited systems, this study, inspired by compressed sensing ...
Bowen Zheng +3 more
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An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher
Entropy, 2022 In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption.
Xiaomeng Song +3 more
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A remark on Compressed Sensing [PDF]
Mathematical Notes, 2007 A classical problem in signal processing is the recovery problem: One is interested in reconstructing a vector \(u \in \mathbb R^m\) from given linear functionals \((u, \phi_j)\), \(j = 1, 2, \ldots, n\), with some known values \(\phi_1, \ldots, \phi_n \in \mathbb R^m\). In most typical applications, \(n\) is substantially smaller than \(m\).
Kashin, B. S., Temlyakov, V. N.
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Intelligent Meta-Imagers: From Compressed to Learned Sensing [PDF]
Applied Physics Reviews, 2021 Computational meta-imagers synergize metamaterial hardware with advanced signal processing approaches such as compressed sensing. Recent advances in artificial intelligence (AI) are gradually reshaping the landscape of meta-imaging. Most recent works use
Chlo'e Saigre-Tardif +4 more
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Distributed Compressed Hyperspectral Sensing Imaging Based on Spectral Unmixing
Sensors, 2020 The huge volume of hyperspectral imagery demands enormous computational resources, storage memory, and bandwidth between the sensor and the ground stations.
Zhongliang Wang, Hua Xiao
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Sensors, 2020 With the widespread application of wireless sensor networks, large-scale systems with high sampling rates are becoming more and more common. The amount of original data generated by the wireless sensor network is very large, and transmitting all the ...
Youtian Qie, Chuangbo Hao, Ping Song
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