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Journal ArticleDOI

Spectral analysis of nonuniformly sampled data -- a review

Prabhu Babu, +1 more
- 01 Mar 2010 - 
- Vol. 20, Iss: 2, pp 359-378
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TLDR
For a given finite set of nonuniformly sampled data, a reasonable way to choose the Nyquist frequency and the resampling time are discussed and the performance of the different methods is evaluated.
About
This article is published in Digital Signal Processing.The article was published on 2010-03-01. It has received 153 citations till now. The article focuses on the topics: Nonuniform sampling & Resampling.

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Citations
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A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics

TL;DR: A comprehensive voxel-based examination of the impact of motion on the BOLD signal suggests that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact.
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Comparison of correlation analysis techniques for irregularly sampled time series

TL;DR: In this article, the authors compare the linear interpolation technique and different approaches for analyzing the correlation functions and persistence of irregularly sampled time series, as Lomb-Scargle Fourier transformation and kernel-based methods.
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New Method of Sparse Parameter Estimation in Separable Models and Its Use for Spectral Analysis of Irregularly Sampled Data

TL;DR: A new semiparametric/sparse method is introduced, called SPICE, which is computationally quite efficient, enjoys global convergence properties, can be readily used in the case of replicated measurements and, unlike most other sparse estimation methods, does not require any subtle choices of user parameters.

OFDM Radar Algorithms in Mobile Communication Networks

TL;DR: OfDM-based radar has been suggested several times independently in the last decade, but many important questions remain unanswered, so one solution is to use OFDM waveforms, which nowadays are commonly used in communications standards already.
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Compressed Sensing of Complex Sinusoids: An Approach Based on Dictionary Refinement

TL;DR: This work model the sparsifying Fourier dictionary as a parameterized dictionary, with the sampled frequency grid points treated as the underlying parameters, and develops a novel recovery algorithm for CS of complex sinusoids based on the philosophy of the variational expectation-maximization (EM) algorithm.
References
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Journal ArticleDOI

Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones

TL;DR: This paper describes how to work with SeDuMi, an add-on for MATLAB, which lets you solve optimization problems with linear, quadratic and semidefiniteness constraints by exploiting sparsity.
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Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data

TL;DR: This paper studies the reliability and efficiency of detection with the most commonly used technique, the periodogram, in the case where the observation times are unevenly spaced to retain the simple statistical behavior of the evenly spaced case.

Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica

TL;DR: The recent completion of drilling at Vostok station in East Antarctica has allowed the extension of the ice record of atmospheric composition and climate to the past four glacial-interglacial cycles.
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Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica

TL;DR: The recent completion of drilling at Vostok station in East Antarctica has allowed the extension of the ice record of atmospheric composition and climate to the past four glacial-interglacial cycles as discussed by the authors.
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Least - squares frequency analysis of unequally spaced data

TL;DR: In this article, the statistical properties of least-squares frequency analysis of unequally spaced data are examined and it is shown that the reduction in the sum of squares at a particular frequency is a X22 variable.