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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Generalized rejection sampling schemes and applications in signal processing [PDF]
Signal Processing, 2010 Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques, such as Markov chain Monte Carlo (MCMC) and particle filters, have become very popular in signal processing over the last years. However, in many problems of practical interest these techniques demand procedures for sampling from probability distributions with ...
Luca Martino, Joaquı́n Mı́guez
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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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Quadrature Demodulation Method for Resolver Signal Processing Under Different Sampling Rate
IEEE Access, 2022 Resolvers are widely used as position sensors to obtain angle information. The resolver requires the excitation signal and its amplitude is modulated by the rotor position.
Pooreum Jang +3 more
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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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Discretely sampled signals and the rough Hoff process
Stochastic Processes and their Applications, 2016 We introduce a canonical method for transforming a discrete sequential data set into an associated rough path made up of lead-lag increments. In particular, by sampling a $d$-dimensional continuous semimartingale $X:[0,1] \rightarrow \mathbb{R}^d$ at a set of times $D=(t_i)$, we construct a piecewise linear, axis-directed process $X^D: [0,1 ...
Guy Flint, Ben Hambly, Terry Lyons
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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
semanticscholar +1 more source
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
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