Results 11 to 20 of about 2,819,720 (335)
Discrete Signal Processing on Graphs: Sampling Theory [PDF]
IEEE Transactions on Signal Processing, 2015 We propose a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory. We show that the perfect recovery is possible for graph signals bandlimited under the graph Fourier transform, and the sampled signal coefficients form a new graph signal, whose ...
Rohan Varma +3 more
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Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review
Frontiers in Neural Circuits, 2021 The nervous systems converts the physical quantities sensed by its primary receptors into trains of events that are then processed in the brain. The unmatched efficiency in information processing has long inspired engineers to seek brain-like approaches ...
Mohammad-Hassan Tayarani-Najaran +1 more
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Adaptive importance sampling in signal processing [PDF]
Digital Signal Processing, 2015 In Bayesian signal processing, all the information about the unknowns of interest is contained in their posterior distributions. The unknowns can be parameters of a model, or a model and its parameters. In many important problems, these distributions are impossible to obtain in analytical form.
Bugallo, Mónica F. +2 more
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Adaptive Graph Signal Processing: Algorithms and Optimal Sampling Strategies [PDF]
IEEE Transactions on Signal Processing, 2018 Submitted to IEEE Transactions on Signal Processing, September ...
Paolo Di Lorenzo +4 more
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Graph Signal Processing: Modulation, Convolution, and Sampling
, 2019 To analyze data supported by arbitrary graphs G, DSP has been extended to Graph Signal Processing (GSP) by redefining traditional DSP concepts like shift, filtering, and Fourier transform among others. This paper revisits modulation, convolution, and sampling of graph signals as appropriate natural extensions of the corresponding DSP concepts.
J. Y. Shi, José M. F. Moura
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Signal Driven Sampling and Filtering : A Promising Approach for Time Varying Signals Processing [PDF]
, 2009 {"references": ["J.W. Mark and T.D. Todd, \"A nonuniform sampling ap-proach to data\ncompression\", IEEE Transactions on Communica-tions, vol. COM-29,\npp. 24-32, January 1981.", "E. Allier, G. Sicard, L. Fesquet and M. Renaudin, \"A new class of asynchronous\nA/D converters based on time quantization\", ASYNC'03,\npp.197-205, May 2003.", "F ...
Saeed Mian Qaisar +2 more
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Graph Signal Processing: Dualizing GSP Sampling in the Vertex and Spectral Domains [PDF]
IEEE Transactions on Signal Processing, 2021 Vertex based and spectral based GSP sampling has been studied recently. The literature recognizes that methods in one domain do not have a counterpart in the other domain.
John Shi, J. Moura
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Pulse-Doppler Signal Processing with Quadrature Compressive Sampling [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2013 Quadrature compressive sampling (QuadCS) is a recently introduced sub-Nyquist sampling scheme for effective acquisition of inphase and quadrature (I/Q) components of sparse radio frequency signals.
Chao Liu +3 more
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Grid-Graph Signal Processing (Grid-GSP): A Graph Signal Processing Framework for the Power Grid [PDF]
IEEE Transactions on Signal Processing, 2021 The underlying theme of this paper is to explore the various facets of power systems data through the lens of graph signal processing (GSP), laying down the foundations of the Grid-GSP framework.
Raksha Ramakrishna, A. Scaglione
semanticscholar +1 more source
Localized nonlinear functional equations and two sampling problems in signal processing
Advances in Computational Mathematics, 2013 Let 1 ≤ p ≤ ∞. In this paper, we consider solving a nonlinear functional equation f (x) = y, where x, y belong to ℓpand f has continuous bounded gradient in an inverse-closed subalgebra of ℬ (ℓ2), the Banach algebra of all bounded linear operators on the
Qiyu Sun
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