1,902 research outputs found

    Perturbed Orthogonal Matching Pursuit

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    Cataloged from PDF version of article.Compressive Sensing theory details how a sparsely represented signal in a known basis can be reconstructed with an underdetermined linear measurement model. However, in reality there is a mismatch between the assumed and the actual bases due to factors such as discretization of the parameter space defining basis components, sampling jitter in A/D conversion, and model errors. Due to this mismatch, a signal may not be sparse in the assumed basis, which causes significant performance degradation in sparse reconstruction algorithms. To eliminate the mismatch problem, this paper presents a novel perturbed orthogonal matching pursuit (POMP) algorithm that performs controlled perturbation of selected support vectors to decrease the orthogonal residual at each iteration. Based on detailed mathematical analysis, conditions for successful reconstruction are derived. Simulations show that robust results with much smaller reconstruction errors in the case of perturbed bases can be obtained as compared to standard sparse reconstruction techniques

    Sparse ground-penetrating radar imaging method for off-the-grid target problem

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    Cataloged from PDF version of article.Spatial sparsity of the target space in subsurface or through-the-wall imaging applications has been successfully used within the compressive-sensing framework to decrease the data acquisition load in practical systems, while also generating high-resolution images. The developed techniques in this area mainly discretize the continuous target space into grid points and generate a dictionary of model data that is used in image-reconstructing optimization problems. However, for targets that do not coincide with the computation grid, imaging performance degrades considerably. This phenomenon is known as the off-grid problem. This paper presents a novel sparse ground-penetrating radar imaging method that is robust for off-grid targets. The proposed technique is an iterative orthogonal matching pursuit-based method that uses gradient-based steepest ascent-type iterations to locate the off-grid target. Simulations show that robust results with much smaller reconstruction errors are obtained for multiple off-grid targets compared to standard sparse reconstruction techniques. (c) 2013 SPIE and IS&

    A robust compressive sensing based technique for reconstruction of sparse radar scenes

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    Cataloged from PDF version of article.Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay–Doppler plane is discretized and FFT techniques are employed to compute matched filter output on this discrete grid. However, for targets whose delay–Doppler values do not coincide with the computation grid, the detection performance degrades considerably. Especially for detecting strong and closely spaced targets this causes miss detections and false alarms. This phenomena is known as the off-grid problem. Although compressive sensing based techniques provide sparse and high resolution results at sub-Nyquist sampling rates, straightforward application of these techniques is significantly more sensitive to the off-grid problem. Here a novel parameter perturbation based sparse reconstruction technique is proposed for robust delay– Doppler radar processing even under the off-grid case. Although the perturbation idea is general and can be implemented in association with other greedy techniques, presently it is used within an orthogonal matching pursuit (OMP) framework. In the proposed technique, the selected dictionary parameters are perturbed towards directions to decrease the orthogonal residual norm. The obtained results show that accurate and sparse reconstructions can be obtained for off-grid multi target cases. A new performance metric based on Kullback–Leibler Divergence (KLD) is proposed to better characterize the error between actual and reconstructed parameter spaces. Increased performance with lower reconstruction errors are obtained for all the tested performance criteria for the proposed technique compared to conventional OMP and 1 minimization techniques. © 2013 Elsevier Inc. All rights reserve

    Comparison between in situ dry matter degradation and in vitro gas production of tannin-containing leaves from four tree species

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    Dry matter (DM) degradation of Glycrrhiza glabra L, Arbutus andrachne, Juniperus communis, and Pistica lentiscus was determined using two different techniques: (i) the in vitro gas production and (ii) the in situ nylon bag degradability technique. Samples were incubated in situ and in vitro for 3, 6, 12, 24, 48, 72 and 96 h. In situ and in vitro DM degradation kinetics were described using the equation y = a + b (1 - e ct). At all incubation times except 3 and 72 h the cumulative gas production of J. communis was significantly lower than that of G. glabra, A. andrachne and P. lentiscus. At 3, 6 and 12 h incubation times the DM disappearance of J. communis was only significantly lower than that of P. lentiscus. At 24 and 48 h incubation times DM disappearance of J. communis was significantly lower than that of A. andrachne and P. lentiscus. There were significant relationships between in vitro gas production and in situ DM disappearance at 24 h and 96 h incubation times. The gas productions at 24 and 96 h incubation explained 51.2 and 52.4% of variation of DM disappearance, respectively. Gas production from the insoluble fraction (b) alone explained 66.4% of the variation of effective DM degradability (EDMD). The inclusion of gas production from quickly soluble fraction (a) and rate constant (c) of gas production in the regression equation did not improve the accuracy of predicting EDMD. It was concluded that in situ DM disappearance parameters of tannin-containing tree leaves such as used in this present study may be predicted from in vitro gas production parameters. South African Journal of Animal Science Vol. 34(4) 2004: 233-24

    SAR image reconstruction by expectation maximization based matching pursuit

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    Cataloged from PDF version of article.Synthetic Aperture Radar (SAR) provides high resolution images of terrain and target reflectivity. SAR systems are indispensable in many remote sensing applications. Phase errors due to uncompensated platform motion degrade resolution in reconstructed images. A multitude of autofocusing techniques has been proposed to estimate and correct phase errors in SAR images. Some autofocus techniques work as a post-processor on reconstructed images and some are integrated into the image reconstruction algorithms. Compressed Sensing (CS), as a relatively new theory, can be applied to sparse SAR image reconstruction especially in detection of strong targets. Autofocus can also be integrated into CS based SAR image reconstruction techniques. However, due to their high computational complexity, CS based techniques are not commonly used in practice. To improve efficiency of image reconstruction we propose a novel CS based SAR imaging technique which utilizes recently proposed Expectation Maximization based Matching Pursuit (EMMP) algorithm. EMMP algorithm is greedy and computationally less complex enabling fast SAR image reconstructions. The proposed EMMP based SAR image reconstruction technique also performs autofocus and image reconstruction simultaneously. Based on a variety of metrics, performance of the proposed EMMP based SAR image reconstruction technique is investigated. The obtained results show that the proposed technique provides high resolution images of sparse target scenes while performing highly accurate motion compensation. (C) 2014 Elsevier Inc. All rights reserved

    Antegradly Performed TEVAR

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    The effect of polyethylene glycol (PEG 8000) supplementation on in vitro gas production kinetics of leaves from tannin containing trees

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    The objective of this study was to determine the effect of inclusion of polyethylene glycol (PEG 8000) during in vitro incubation on gas production kinetics, organic matter digestibility (OMD) and the metabolisable energy (ME) content of foliage from the tannin containing tree species, Pistica lentiscus, Arbutus andrachne and Juniperus communis. The amount of gas produced when the foliage was incubated with buffered rumen fluid, was determined after 0, 3, 6, 12, 24, 48, 72 and 96 h of incubation in the presence of PEG at inclusions rates of 15, 30, 60 and 90 mg and in the absence of PEG. Their kinetics were described using the equation p = a + b (1-e-ct). Addition of PEG resulted in an increased gas production at almost all incubation times in all tree species. However species showed variable responses. After 3 h of incubation the PEG addition showed no significant effect on gas production when the foliage from A. andrachne was incubated, but had a significant effect on gas production as duration of incubation extended. The increase in gas production in response to increased levels of PEG inclusion was linear for P. lentiscus and J. communis. However, when the PEG inclusion rates exceeded 60 mg there was no significant increase in gas production when A. andrachne was incubated. The estimated parameters such as gas production rate(c) and gas production (a) from the immediately soluble fraction were not affected by the level PEG treatment, except that PEG addition at 90 mg had a significant effect on the gas production (a) from immediately soluble fraction of leaves of J. communis. Gas production (b) from the insoluble fraction (mL) and potential gas production (a+b), OMD and ME of tree leaves increased significantly with increasing levels of PEG addition. However, when PEG inclusion exceeded 60 mg these parameters showed no significant increase when leaves from A. andrachne were incubated. Although the mean increase in OMD per mg PEG supplementation was 0.131 digestibility units, the increase in ME per mg PEG supplementation was 0.0201 ME units. The elevated levels of gas produced, and increased OMD and ME estimates with the inclusion of PEG demonstrated the negative effect of tannins in foliage on digestibility. South African Journal of Animal Science Vol. 35(4) 2005: 229-23

    Effect of cultivar and formaldehyde treatment of barley grain on rumen fermentation characteristics using in vitro gas production

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    The aim of this study was to determine the effects of cultivar and formaldehyde treatment of barley grains on rumen fermentation characteristics using the in vitro gas production technique. Amount of gas produced (mL/g organic matter (OM)) during fermentation was determined after 0, 3, 6, 12, 24, 48, 72 and 96 h of incubation in buffered rumen fluid. The gas production kinetics were described using the equation: y = A {1 – exp [- b (t-T) – c (√t - √T)]} where b and c are the initial gas production rate constant (h-1) and later gas production rate constant (h-1/2), respectively. Cultivar and formaldehyde treatment had significant effects on gas production kinetics. Total gas production (A) ranged from 389.9 to 410.8 (mL/g OM) with the cultivar, Esterel, producing the largest volume of gas of the cultivars. Due to low gas production rates at 3, 6 and 12 h of incubation the cultivars, Viva and Cecilla, took the longest to produce 50% of their total volume of gas. Formaldehyde treatment reduced the rate (μ) of gas production at 3, 6 and 12 h of incubation, and the total volume of gas (A), but increased the time (h) to produce 50% of A and reduced the time (h) to produce 95% of A. The reduction in gas production ranged from 33.3 to 51 mL/g OM with 6 h incubation showing the highest decrease in gas production. It is concluded that formaldehyde treatment may provide an opportunity to manipulate the site of digestion of barley grain in the digestive tract of ruminants. Through the selection of suitable cultivars and through formaldehyde treatment the nutritional and health problems associated with the fermentation of barley grain in the rumen could be reduced. Keywords: Barley cultivars; formaldehyde treatment; gas production kinetics South African Journal of Animal Sciences Vol. 35 (3) 2005: pp.206-21

    Sparse delay-Doppler image reconstruction under off-grid problem

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    Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay-Doppler plane is discretized and FFT techniques are employed to compute matched filter output on this discrete grid. However, for targets whose delay-Doppler values do not coincide with the computation grid, the detection performance degrades considerably. Especially for detecting strong and closely spaced targets this causes miss detections and false alarms. Although compressive sensing based techniques provide sparse and high resolution results at sub-Nyquist sampling rates, straightforward application of these techniques is significantly more sensitive to the off-grid problem. Here a novel and OMP based sparse reconstruction technique with parameter perturbation, named as PPOMP, is proposed for robust delay-Doppler radar processing even under the off-grid case. In the proposed technique, the selected dictionary parameters are perturbed towards directions to decrease the orthogonal residual norm. A new performance metric based on Kull-back-Leibler Divergence (KLD) is proposed to better characterize the error between actual and reconstructed parameter spaces. © 2014 IEEE

    A recursive way for sparse reconstruction of parametric spaces

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    A novel recursive framework for sparse reconstruction of continuous parameter spaces is proposed by adaptive partitioning and discretization of the parameter space together with expectation maximization type iterations. Any sparse solver or reconstruction technique can be used within the proposed recursive framework. Experimental results show that proposed technique improves the parameter estimation performance of classical sparse solvers while achieving Cramér-Rao lower bound on the tested frequency estimation problem. © 2014 IEEE
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