Object
Title: Optimal random sampling for spectrum estimation in dasp applications
Contributor:
Beliczyński, Bartłomiej - red.
Subtitle:
Intelligent Control and Signal Processing
Group publication title:
Abstract:
In this paper we analyse a class of DASP (Digital Alias-free Signal Processing) methods for spectrum estimation of sampledsignals. These methods consist in sampling the processed signals at randomly selected time instants. We construct estimatorsof Fourier transforms of the analysed signals. ; The estimators are unbiased inside arbitrarily wide frequency ranges,regardless of how sparsely the signal samples are collected. In order to facilitate quality assessment of the estimators, wecalculate their standard deviations. The optimal sampling scheme that minimises the variance of the resulting estimator isderived. The further analysis presented in this paper shows how sampling instant jitter deteriorates the quality of spectrumestimation. A couple of numerical examples illustrate the main thesis of the paper.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Resource Identifier:
Pages:
Source:
AMCS, Volume 15, Number 4 (2005) ; click here to follow the link
Language:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS)
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2005)
Last modified:
Sep 7, 2021
In our library since:
Aug 9, 2018
Number of object content hits:
88
All available object's versions:
https://zbc.uz.zgora.pl/publication/54896
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International Journal of Applied Mathematics and Computer Science (AMCS)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 25 (2015)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 24 (2014)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 23 (2013)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 22 (2012)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 21 (2011)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 20 (2010)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 19 (2009)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 17 (2007)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 16 (2006)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15 (2005)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15, number 1 (2005)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15, number 2 (2005)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15, number 3 (2005)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15, number 4 (2005)
- International Journal of Applied Mathematics and Computer Science (AMCS), volume 15, number 4 (2005) - spis treści
- Observer design for systems with unknown inputs
- Realization problem for a class of positive continuous-time systems with delays
- Stability of a class of adaptive nonlinear systems
- Optimal random sampling for spectrum estimation in dasp applications
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
| Edition name | Date |
|---|---|
| Optimal random sampling for spectrum estimation in dasp applications | Sep 7, 2021 |
