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On Digital Signal Processing of Time Series for Spectrum Estimation. [PDF]

IEEE Trans Instrum Meas
Gu D, Rezac J, Lu X, Kuester D.
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An explainable hybrid framework for early detection of cardiovascular diseases using Categorical Boosting and Bees algorithm. [PDF]

Sci Rep
Sen J, Bhattacharya S.
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Enhancing smart home environments: a novel pattern recognition approach to ambient acoustic event detection and localization. [PDF]

Front Big Data
Shabbir A, Butt AH, Khan T, Chiari L, Almadhor A, Karovic V.   +5 more
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Learning stochastic processes with intrinsic noise from cross-sectional biological data. [PDF]

Proc Natl Acad Sci U S A
Maddu S, Chardès V, Shelley MJ.
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Inverse mapping of quantum properties to structures for chemical space of small organic molecules. [PDF]

Nat Commun
Fallani A, Medrano Sandonas L, Tkatchenko A.   +2 more
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Global well-posedness and interior regularity of 2D Navier-Stokes equations with stochastic boundary conditions. [PDF]

Math Ann
Agresti A, Luongo E.
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Weakly interpolating subspaces

Numerical Functional Analysis and Optimization, 1983
A study is made of those n-dimensional subspaces G of C 0(T) which are weakly interpolating. They are more general than the classical Haar or Chebyshev subspaces, or the weak Chebyshev subspaces considered in [2]. Weakly interpolating subspaces G have the property that for each feC0(T) which has a unique best approximation g0 e G, the error f - g0 has ...
Nürnberger, Günther, Deutsch, Frank
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Interpolation Filter Model For Ramanujan Subspace Signals

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
Ramanujan sums have been shown to have interesting applications in signal processing. Ramanujan subspaces, Ramanujan dictionaries, and Ramanujan filter banks are useful in representing and denoising discrete-time periodic signals. In this paper, we theoretically investigate an ideal interpolation filter model for Ramanujan subspace signals wherein an ...
Kulkarni, Pranav, Vaidyanathan, P. P.
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