Efficient numerical methods in non-uniform sampling theory
Numerische Mathematik
Spectrum: spectral analysis of unevenly spaced paleoclimatic time series
Computers & Geosciences
Spectral analysis with incomplete time series: an example from seismology
Computers & Geosciences
Autoregression and irregular sampling: spectral estimation
Signal Processing
Automatic spectral analysis with missing data
Digital Signal Processing
Spectral analysis of irregularly-sampled data: Paralleling the regularly-sampled data approaches
Digital Signal Processing
Spectral analysis of nouniformly sampled data: a new approach versus the periodogram
IEEE Transactions on Signal Processing
Blind multiband signal reconstruction: compressed sensing for analog signals
IEEE Transactions on Signal Processing
Nonparametric spectral analysis with missing data via the EM algorithm
Digital Signal Processing
Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter
IEEE Transactions on Signal Processing
Autoregressive spectral analysis when observations are missing
Automatica (Journal of IFAC)
IEEE Transactions on Information Theory
Poisson sampling and spectral estimation of continuous-time processes
IEEE Transactions on Information Theory
Periodic pattern analysis of non-uniformly sampled stock market data
Intelligent Data Analysis
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In this paper, we present a comprehensive review of methods for spectral analysis of nonuniformly sampled data. For a given finite set of nonuniformly sampled data, a reasonable way to choose the Nyquist frequency and the resampling time are discussed. The various existing methods for spectral analysis of nonuniform data are grouped and described under four broad categories: methods based on least squares; methods based on interpolation techniques; methods based on slotted resampling; methods based on continuous time models. The performance of the methods under each category is evaluated on simulated data sets. The methods are then classified according to their capabilities to handle different types of spectrum, signal models and sampling patterns. Finally the performance of the different methods is evaluated on two real life nonuniform data sets. Apart from the spectral analysis methods, methods for exact signal reconstruction from nonuniform data are also reviewed.