Influence of Signal Stationarity on Digital Stochastic Measurement Implementation
The paper presents the influence of signal stationarity on digital stochastic measurement method implementation. The implementation method is based on stochastic voltage generators, analog adders, low resolution A/D converter, and multipliers and accumulators implemented by Field-Programmable Gate A...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Banja Luka
2013-06-01
|
| Series: | Electronics |
| Subjects: | |
| Online Access: | http://electronics.etfbl.net/journal/Vol17No1/xPaper_07.pdf |
| _version_ | 1818034789016403968 |
|---|---|
| author | Ivan Župunski Marjan Urekar Nebojša Pjevalica Dragan Pejić Vladimir Vujičić Platon Sovilj |
| author_facet | Ivan Župunski Marjan Urekar Nebojša Pjevalica Dragan Pejić Vladimir Vujičić Platon Sovilj |
| author_sort | Ivan Župunski |
| collection | DOAJ |
| description | The paper presents the influence of signal stationarity on digital stochastic measurement method implementation. The implementation method is based on stochastic voltage generators, analog adders, low resolution A/D converter, and multipliers and accumulators implemented by Field-Programmable Gate Array (FPGA). The characteristic of first implementations of digital stochastic measurement was the measurement of stationary signal harmonics over the constant measurement period. Later, digital stochastic measurement was extended and used also when it was necessary to measure timeseries of non-stationary signal over the variable measurement time. The result of measurement is the set of harmonics, which is, in the case of non-stationary signals, the input for calculating digital values of signal in time domain. A theoretical approach to determine measurement uncertainty is presented and the accuracy trends with varying signal-to-noise ratio (SNR) are analyzed. Noisy brain potentials (spontaneous and nonspontaneous) are selected as an example of real non-stationary signal and its digital stochastic measurement is tested by simulations and experiments. Tests were performed without noise and with adding noise with SNR values of 10dB, 0dB and - 10dB. The results of simulations and experiments are compared versus theory calculations, and comparasion confirms the theory. |
| first_indexed | 2024-12-10T06:44:44Z |
| format | Article |
| id | doaj.art-1df3ca8a262146c3a6112a103838bef5 |
| institution | Directory Open Access Journal |
| issn | 1450-5843 |
| language | English |
| last_indexed | 2024-12-10T06:44:44Z |
| publishDate | 2013-06-01 |
| publisher | University of Banja Luka |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-1df3ca8a262146c3a6112a103838bef52022-12-22T01:58:40ZengUniversity of Banja LukaElectronics1450-58432013-06-01171455310.7251/ELS1317045SInfluence of Signal Stationarity on Digital Stochastic Measurement ImplementationIvan ŽupunskiMarjan UrekarNebojša PjevalicaDragan PejićVladimir VujičićPlaton SoviljThe paper presents the influence of signal stationarity on digital stochastic measurement method implementation. The implementation method is based on stochastic voltage generators, analog adders, low resolution A/D converter, and multipliers and accumulators implemented by Field-Programmable Gate Array (FPGA). The characteristic of first implementations of digital stochastic measurement was the measurement of stationary signal harmonics over the constant measurement period. Later, digital stochastic measurement was extended and used also when it was necessary to measure timeseries of non-stationary signal over the variable measurement time. The result of measurement is the set of harmonics, which is, in the case of non-stationary signals, the input for calculating digital values of signal in time domain. A theoretical approach to determine measurement uncertainty is presented and the accuracy trends with varying signal-to-noise ratio (SNR) are analyzed. Noisy brain potentials (spontaneous and nonspontaneous) are selected as an example of real non-stationary signal and its digital stochastic measurement is tested by simulations and experiments. Tests were performed without noise and with adding noise with SNR values of 10dB, 0dB and - 10dB. The results of simulations and experiments are compared versus theory calculations, and comparasion confirms the theory.http://electronics.etfbl.net/journal/Vol17No1/xPaper_07.pdfDigital measurementsstochastic measurementsmeasurement uncertaintybrain potentials |
| spellingShingle | Ivan Župunski Marjan Urekar Nebojša Pjevalica Dragan Pejić Vladimir Vujičić Platon Sovilj Influence of Signal Stationarity on Digital Stochastic Measurement Implementation Electronics Digital measurements stochastic measurements measurement uncertainty brain potentials |
| title | Influence of Signal Stationarity on Digital Stochastic Measurement Implementation |
| title_full | Influence of Signal Stationarity on Digital Stochastic Measurement Implementation |
| title_fullStr | Influence of Signal Stationarity on Digital Stochastic Measurement Implementation |
| title_full_unstemmed | Influence of Signal Stationarity on Digital Stochastic Measurement Implementation |
| title_short | Influence of Signal Stationarity on Digital Stochastic Measurement Implementation |
| title_sort | influence of signal stationarity on digital stochastic measurement implementation |
| topic | Digital measurements stochastic measurements measurement uncertainty brain potentials |
| url | http://electronics.etfbl.net/journal/Vol17No1/xPaper_07.pdf |
| work_keys_str_mv | AT ivanzupunski influenceofsignalstationarityondigitalstochasticmeasurementimplementation AT marjanurekar influenceofsignalstationarityondigitalstochasticmeasurementimplementation AT nebojsapjevalica influenceofsignalstationarityondigitalstochasticmeasurementimplementation AT draganpejic influenceofsignalstationarityondigitalstochasticmeasurementimplementation AT vladimirvujicic influenceofsignalstationarityondigitalstochasticmeasurementimplementation AT platonsovilj influenceofsignalstationarityondigitalstochasticmeasurementimplementation |