Results 21 to 30 of about 78,363 (276)
Further Results on Performance Analysis for Compressive Sensing Using Expander Graphs [PDF]
, 2007 Compressive sensing is an emerging technology which can recover a sparse signal vector of dimension n via a much smaller number of measurements than n. In this paper, we will give further results on the performance bounds of compressive sensing.
Hassibi, Babak, Xu, Weiyu
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Nonlinear Compressive Particle Filtering [PDF]
, 2013 Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent problems. This approach has two disadvantages. Firstly, the temporal dependency in the
Ohlsson, Henrik +2 more
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SPECTRUM SENSING OF WIDE BAND SIGNALS BASED ON ENERGY DETECTION WITH COMPRESSIVE SENSING
Journal of Engineering and Sustainable Development, 2020 Compressive sensing (CS) technique is used to solve the problem of high sampling rate with wide band signal spectrum sensing where high speed analogue to digital converter is needed to do that. This leads to difficult hardware implementation, large time
Ali Mohammad A. AL-Hussain +1 more
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Deterministic Sensing Matrices in Compressive Sensing: A Survey
The Scientific World Journal, 2013 Compressive sensing is a sampling method which provides a new approach to efficient signal compression and recovery by exploiting the fact that a sparse signal can be suitably reconstructed from very few measurements.
Thu L. N. Nguyen, Yoan Shin
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Jurnal Elkomika, 2020 ABSTRAK Watermarking pada citra medis dilakukan untuk melindungi hak kepemilikan dan keaslian sebuah citra medis. Proses embedding dan extraction dirancang menggunakan metode Stationary Wavelet Transform (SWT) dan Statistical Mean Manipulation (SMM ...
YASQI HAFIZHANA +3 more
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SoftwareX, 2018 Compressive sensing is a computational framework for acquisition and processing of sparse signals at sampling rates below the rates mandated by the Nyquist sampling theorem.
Ervin Sejdić +2 more
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Task-Driven Adaptive Statistical Compressive Sensing of Gaussian Mixture Models [PDF]
, 2012 A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing.
Carin, Lawrence +3 more
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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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A New Method for EEG Compressive Sensing
Advances in Electrical and Computer Engineering, 2012 The paper investigates the possibility of using compressive sensing techniques for the acquisition and reconstruction of EEG signals containing the evoked potential P300. A method of EEG compressive sensing based on the physiological correlation of EEG
FIRA, M., GORAS, L.
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Sensors, 2014 Compressive Sensing Imaging (CSI) is a new framework for image acquisition, which enables the simultaneous acquisition and compression of a scene. Since the characteristics of Compressive Sensing (CS) acquisition are very different from traditional image
Xiangwei Li +4 more
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