Proceedings ArticleDOI
Analysis of algorithms for nonuniform-time discrete Fourier transform
D.M. Bland,Timo Laakso,Andrzej Tarczynski +2 more
- Vol. 2, pp 453-456
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TLDR
The proposed algorithms for NUT-DFT are based on approximating the continuous-time Fourier transform by different numerical integration algorithms and special attention is paid to the ability of the transform to capture signals with frequency components above half the average sampling rate.Abstract:
In order to perform spectral analysis of nonuniformly sampled time domain signals, algorithms for the Nonuniform-Time Discrete Fourier Transform (NUT-DFT) are developed and evaluated The NUT-DFT takes nonuniform time domain data and produces a uniform sampled spectrum. The proposed algorithms for NUT-DFT are based on approximating the continuous-time Fourier transform by different numerical integration algorithms. Special attention is paid to the ability of the transform to capture signals with frequency components above half the average sampling rate. The performance of the algorithms is studied experimentally by analysing both nonuniformly and uniformly sampled data.read more
Citations
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Journal ArticleDOI
Spectral analysis of randomly sampled signals: suppression of aliasing and sampler jitter
Andrzej Tarczynski,Najib Allay +1 more
TL;DR: Two DASP approaches for spectrum estimation of continuous-time signals are presented, named the weighted sample (WS) and weighted probability (WP) density functions, respectively, which utilize random sampling to suppress aliasing and produce unbiased estimators of the signal spectrum.
Non-Uniform Sampling in Statistical Signal Processing
TL;DR: This work outlines three approaches to decimate non-uniformly sampled signals, which are all based on interpolation, and computes an approximate Fourier transform, after which truncation and IFFT give the desired result.
Journal ArticleDOI
Frequency Response Enhancement by Periodical Nonuniform Sampling in Distributed Sensing
TL;DR: In this paper, the authors proposed a method to significantly extend the frequency response range of phase-sensitive optical time domain reflectometry ( $\varphi $ -OTDR) systems by impressing vibration signals on a set of backscattering signals that are carried by different wavelengths within one measurement interval.
Journal ArticleDOI
Frequency Domain Analysis of Signals With Stochastic Sampling Times
TL;DR: The main result gives the prior distribution of several AFTs expressed in terms of the true Fourier transform and variants of the characteristic function of the sampling time distribution, which extends leakage and alias suppression with bias and variance terms due to NUS.
Journal ArticleDOI
Estimation and inversion of the effects of cell population asynchrony in gene expression time-series
Harri Lähdesmäki,Heikki Huttunen,Tommi Aho,Marja-Leena Linne,Jari Niemi,Juha Kesseli,Ronald K. Pearson,Olli Yli-Harja +7 more
TL;DR: Several approaches to improve the quality of gene expression data obtained from time-series measurements by applying signal processing tools are introduced, concentrating especially on a smoothing effect caused by the distribution of the cell population in time and introducing several methods for inverting this phenomenon.
References
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Journal ArticleDOI
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.
Journal ArticleDOI
The Shannon sampling theorem—Its various extensions and applications: A tutorial review
TL;DR: In this paper, the authors present the various contributions made for the sampling theorems with the necessary mathematical details to make it self-contained, including sampling for functions of more than one variable, random processes, nonuniform sampling, nonband-limited functions, implicit sampling, sampling with the function and its derivatives as suggested by Shannon in his original paper, and sampling for general integral transforms.