I.I.D. stochastic analysis of PWM signals

Noyan C. Sevüktekin; Andrew C. Singer

doi:10.1109/ACSSC.2014.7094796

I.I.D. stochastic analysis of PWM signals

Noyan C. Sevüktekin
, Andrew C. Singer

Office of the Dean of the College of Engineering and Applied Sciences

University of Illinois at Urbana-Champaign

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

A stochastic analysis for pulse width modulation (PWM) is given. Under a discrete random generator process with independent identically distributed (i.i.d.), continuous, range-limited samples, stochastic models for different PWM signals are proposed. Using randomization of the signal starting point, wide sense stationarity (WSS) of proposed PWM signals are shown. Autocorrelation functions and their corresponding power spectrum densities (PSD) are derived in terms of the modified complementary cumulative distribution function of i.i.d samples. For the case where the samples are i.i.d. uniformly distributed, the proposed autocorrelation functions are tested with simulations.

Original language	English
Title of host publication	Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	1885-1889
Number of pages	5
ISBN (Electronic)	9781479982974
DOIs	https://doi.org/10.1109/ACSSC.2014.7094796
State	Published - Apr 24 2015
Event	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States Duration: Nov 2 2014 → Nov 5 2014

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2015-April
ISSN (Print)	1058-6393

Conference

Conference	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/Territory	United States
City	Pacific Grove
Period	11/2/14 → 11/5/14

Access to Document

10.1109/ACSSC.2014.7094796

Cite this

Sevüktekin, N. C., & Singer, A. C. (2015). I.I.D. stochastic analysis of PWM signals. In M. B. Matthews (Ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers (pp. 1885-1889). Article 7094796 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2014.7094796

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title = "I.I.D. stochastic analysis of PWM signals",

abstract = "A stochastic analysis for pulse width modulation (PWM) is given. Under a discrete random generator process with independent identically distributed (i.i.d.), continuous, range-limited samples, stochastic models for different PWM signals are proposed. Using randomization of the signal starting point, wide sense stationarity (WSS) of proposed PWM signals are shown. Autocorrelation functions and their corresponding power spectrum densities (PSD) are derived in terms of the modified complementary cumulative distribution function of i.i.d samples. For the case where the samples are i.i.d. uniformly distributed, the proposed autocorrelation functions are tested with simulations.",

author = "Sev{\"u}ktekin, \{Noyan C.\} and Singer, \{Andrew C.\}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 ; Conference date: 02-11-2014 Through 05-11-2014",

year = "2015",

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doi = "10.1109/ACSSC.2014.7094796",

language = "English",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

publisher = "IEEE Computer Society",

pages = "1885--1889",

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booktitle = "Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers",

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Sevüktekin, NC & Singer, AC 2015, I.I.D. stochastic analysis of PWM signals. in MB Matthews (ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers., 7094796, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2015-April, IEEE Computer Society, pp. 1885-1889, 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, Pacific Grove, United States, 11/2/14. https://doi.org/10.1109/ACSSC.2014.7094796

I.I.D. stochastic analysis of PWM signals. / Sevüktekin, Noyan C.; Singer, Andrew C.
Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers. ed. / Michael B. Matthews. IEEE Computer Society, 2015. p. 1885-1889 7094796 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Singer, Andrew C.

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N2 - A stochastic analysis for pulse width modulation (PWM) is given. Under a discrete random generator process with independent identically distributed (i.i.d.), continuous, range-limited samples, stochastic models for different PWM signals are proposed. Using randomization of the signal starting point, wide sense stationarity (WSS) of proposed PWM signals are shown. Autocorrelation functions and their corresponding power spectrum densities (PSD) are derived in terms of the modified complementary cumulative distribution function of i.i.d samples. For the case where the samples are i.i.d. uniformly distributed, the proposed autocorrelation functions are tested with simulations.

AB - A stochastic analysis for pulse width modulation (PWM) is given. Under a discrete random generator process with independent identically distributed (i.i.d.), continuous, range-limited samples, stochastic models for different PWM signals are proposed. Using randomization of the signal starting point, wide sense stationarity (WSS) of proposed PWM signals are shown. Autocorrelation functions and their corresponding power spectrum densities (PSD) are derived in terms of the modified complementary cumulative distribution function of i.i.d samples. For the case where the samples are i.i.d. uniformly distributed, the proposed autocorrelation functions are tested with simulations.

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M3 - Conference contribution

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PB - IEEE Computer Society

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Y2 - 2 November 2014 through 5 November 2014

ER -

I.I.D. stochastic analysis of PWM signals

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