Recognizing different types of stochastic processes

dc.creatorKim, Jong U.
dc.creatorKish, Laszlo B.
dc.date2005-10-12
dc.date.accessioned2026-07-07T06:48:26Z
dc.date.available2026-07-07T06:48:26Z
dc.descriptionWe propose a new cross-correlation method that can recognize independent realizations of the same type of stochastic processes and can be used as a new kind of pattern recognition tool in biometrics, sensing, forensic, security and image processing applications. The method, which we call bispectrum correlation coefficient method, makes use of the cross-correlation of the bispectra. Three kinds of cross-correlation coefficients are introduced. To demonstrate the new method, six different random telegraph signals are tested, where four of them have the same power density spectrum. It is shown that the three coefficients can map the different stochastic processes to specific sub-volumes in a cube.
dc.description6 pages
dc.identifierhttps://arxiv.org/abs/physics/0510118
dc.identifierhttp://arxiv.org/abs/physics/0510118
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/103998
dc.subjectData Analysis, Statistics and Probability
dc.titleRecognizing different types of stochastic processes
dc.typetext

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