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In this paper we propose novel methods for completion (from limited samples) and de-noising of multilinear (tensor) data and as an application consider 3-D and 4- D (color) video data completion and de-noising. We exploit the recently proposed tensor-Singular Value Decomposition (t-SVD)[11]. Based on t-SVD, the notion of multilinear rank and a related(More)
B. P. Abbott, R. Abbott, R. Adhikari, P. Ajith, B. Allen, G. Allen, R. S. Amin, S. B. Anderson, W.G. Anderson, M.A. Arain, M. Araya, H. Armandula, P. Armor, Y. Aso, S. Aston, P. Aufmuth, C. Aulbert, S. Babak, P. Baker, S. Ballmer, C. Barker, D. Barker, B. Barr, P. Barriga, L. Barsotti, M.A. Barton, I. Bartos, R. Bassiri, M. Bastarrika, B. Behnke, M.(More)
B. Abbott, R. Abbott, R. Adhikari, P. Ajith, B. Allen, G. Allen, R. Amin, D. P. Anderson, S. B. Anderson, W.G. Anderson, M.A. Arain, M. Araya, H. Armandula, P. Armor, Y. Aso, S. Aston, P. Aufmuth, C. Aulbert, S. Babak, S. Ballmer, H. Bantilan, B. C. Barish, C. Barker, D. Barker, B. Barr, P. Barriga, M.A. Barton, M. Bastarrika, K. Bayer, J. Betzwieser, P. T.(More)
B. P. Abbott, R. Abbott, R. Adhikari, P. Ajith, B. Allen, G. Allen, R. S. Amin, S. B. Anderson, W.G. Anderson, M.A. Arain, M. Araya, H. Armandula, P. Armor, Y. Aso, S. Aston, P. Aufmuth, C. Aulbert, S. Babak, P. Baker, S. Ballmer, C. Barker, D. Barker, B. Barr, P. Barriga, L. Barsotti, M.A. Barton, I. Bartos, R. Bassiri, M. Bastarrika, B. Behnke, M.(More)
In this paper we present novel strategies for completion of 5D pre-stack seismic data, viewed as a 5D tensor or as a set of 4D tensors across temporal frequencies. In contrast to existing complexity penalized algorithms for seismic data completion, which employ matrix analogues of tensor decompositions such as HOSVD or use overlapped Schatten norms from(More)
In this paper we propose novel methods for compression and recovery of multilinear data under limited sampling. We exploit the recently proposed tensorSingular Value Decomposition (t-SVD)[1], which is a group theoretic framework for tensor decomposition. In contrast to popular existing tensor decomposition techniques such as higher-order SVD (HOSVD), t-SVD(More)
This paper presents several strategies for spectral de-noising of hyperspectral images and hypercube reconstruction from a limited number of tomographic measurements. In particular we show that the non-noisy spectral data, when stacked across the spectral dimension, exhibits low-rank. On the other hand, under the same representation, the spectral noise(More)
A search for periodic gravitational waves, from sources such as isolated rapidly-spinning neutron stars, was carried out using 510 hours of data from the fourth LIGO science run (S4). The search was for quasi-monochromatic waves in the frequency range from 50 Hz to 1500 Hz, with a linear frequency drift ˙ f (measured at the solar system barycenter) in the(More)
In this work we propose a novel algorithm for multiple-event localization for Hydraulic Fracture Monitoring (HFM) through the exploitation of the sparsity of the observed seismic signal when represented in a basis consisting of space time propagators. We provide explicit construction of these propagators using a forward model for wave propagation which(More)
Accurate seismic hydraulic fracturing monitoring (HFM) can mitigate many of the environmental impacts by providing a clear real-time image of where the fractures are occurring outside of the shale and how efficiently they are formed within the gas deposit. Although simple in principle, real time monitoring of hydraulic fracturing is extremely difficult to(More)