High Dimensional Geometry for Compressive Sensing
Efficient two dimensional compressive sensing in MIMO radar
... We have introduced a new 1D and 2D CS model for a pulse-Doppler collocated MIMO radar. Then, we di- vided the measurement matrix design into four cases in which the measurement matrices applied to receivers and pulses ...
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Four-Dimensional SAR Imaging Scheme Based on Compressive Sensing
... 5. CONCLUSION 4-D SAR imaging is an extension of the conventional microwave imaging technique. It extends the potentialities of SAR tomography to the target deformation monitoring, which enables not only separating ...
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SOME GEOMETRY IN HIGH-DIMENSIONAL SPACES
... infinite dimensional spaces need not always be completely mysterious; sometimes one lucks out and can watch a “coun- terintuitive” phenomenon developing in R n for large ...
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COMPRESSIVE SENSING
... However, even though the problem of L1-minimisation has almost the same form as the L2- minimisation, it’s much harder to solve. Because this problem doesn’t have a smooth function, the trick we used to solve L2-problem ...
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Dimension reduction algorithms for near-optimal low-dimensional embeddings and compressive sensing
... Secondly, motivated by compressive sensing of images, we examine linear embeddings of datasets containing points that are sparse in the pixel basis, with the goal o[r] ...
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Compressive sensing in dynamic scenes
... For example, when a picture is taken with a digital camera, dozens of megabytes of data are collected. However, it turns out that when this image is transformed to e.g. the wavelet domain (as is done by the well-known ...
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COMPRESSIVE SENSING BY RANDOM CONVOLUTION
... extremely high probability, it will not change the norm of an arbitrary vector too ...to compressive sampling, as it would require us to randomly combine on the order of m samples of Hx 0 from arbitrary ...
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Lensless Compressive Sensing Imaging
... lensless compressive sensing imaging ...two dimensional array of aperture ...A compressive sensing matrix is implemented by adjusting the transmittance of the individual aperture ...
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Compressive Sensing for Background Subtraction
... Abstract. Compressive sensing (CS) is an emerging field that provides a frame- work for image recovery using sub-Nyquist sampling ...low dimensional compressed representation of it, which is ...
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Compressive Sensing Based Channel Estimation for High-order MIMO Systems
... 6 Conclusions In this paper, we propose a CS based scheme for channel estimation in high-order MIMO system. An accurate channel estimation is obtained with short pilot sequence. The key idea of the scheme is using ...
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High Resolution Spectral Estimation using BP via Compressive Sensing
... via Compressive Sensing Isabel ...compressed sensing (CS) for estimating the spectrum of a signal written as a linear combination of a small number of ...
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High-Dimensional Geometry of Sliding Window Embeddings of Periodic Videos
... [email protected] Abstract We explore the high dimensional geometry of sliding windows of periodic videos. Under a reas- onable model for periodic videos, we show that the sliding window is ...
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High dimensional phenomena : dilations, tensor products and geometry of L₁
... Abstract The purpose of this dissertation is to study several problems related to high- dimensional phenomena in analysis, geometry and probability. The first problem examines the behaviour of ...
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Advanced imaging via multiplexed sensing and compressive sensing
... three-dimensional compressive sensing (3DCS) cam- era, which can reduce the required the sampling rate for video acquisition to a practical level ...
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Analysis of compressive sensing for hyperspectral remote sensing applications
... very high NDVI thresholds, there is some disagreement between NDVI results from traditional HSI and CS images where r ≤ 50%, however the general regions where dense and healthy vegetation are identified remain the ...
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Speech Enhancement Using Compressive Sensing
... enhancement, Compressive sensing, DCT, l1 –minimization, Measurement ...emerging compressive sensing theory shows that an unevenly sampled discrete signal can be perfectly reconstructed by ...
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Dictionary Design for Distributed Compressive Sensing
... The convergence behaviour of different algorithms, i.e., suc- cess recovery rate of the ground truth dictionary (averaged over 10 trials) versus the number of iterations is shown in Fig. 1. It can be seen that the ...
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Correlated Compressive Sensing for Networked Data
... of high-dimensional data over the last two decades is their inherent spar- sity (Cand`es and Wakin, ...sparsity, Compressive Sensing (CS) (Donoho, 2006) has been developed to collect ...
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Exploiting Memristors for Compressive Sensing Applications
... detailed view, and each embedded figure shows the overall curve from 0 to 13nm. Specifically, Fig. 3.6a shows the impact of individual parameter separately on device variations, whereas Fig. 3.6b shows the overall effect ...
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A Cognitive Radio Compressive Sensing Framework
... like high sampling rates and low number of available samples due to the stringent timing ...requirements. Compressive sensing (CS) is a new signal acquisition paradigm for signals being sparse in ...
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