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dc.contributor.advisor Johnson, Don H.
dc.creatorSwami, Ananthram
dc.date.accessioned 2018-12-18T21:24:08Z
dc.date.available 2018-12-18T21:24:08Z
dc.date.issued 1980
dc.identifier.urihttps://hdl.handle.net/1911/104494
dc.description.abstract The multiplicative intensity model for the intensity function u(t;N(t);w) = v(t)r(t - of a self-exciting point process is analyzed in terms of the distortion of v(t) by the channel r(x). A convenient and common method of presenting point process data, the Post Stimulus Histogram is shown to be related to the ensemble average of the intensity process and hence incorporates stimulus v() as well as refractory r() related effects. This quantity is not usually amenable to closed-form representation. We propose an approximation to the PST which is reasonably good under specified conditions. A maximum likelihood estimator of r(x), where v(t) is known, is derived. A maximum likelihood estimator of v(t), given r(x), is also derived. This estimator is meaningful only when the signal v(t) is known to be periodic. The M.L. Estimator compensates for relative dead-time effects. We propose an iterative dead-time processor, which operating on the histogram obtained from the M.L. Estimate, partially compensates for absolute dead-time effects. The performance of these estimators is compared with those of other procedures. Applications to spike trains recorded from auditory neurons are discussed.
dc.format.extent 110 pp
dc.language.iso eng
dc.title Estimation techniques in non-stationary renewal processes
dc.identifier.digital RICE2129
dc.contributor.committeeMember Parks, Thomas W.;Thompson, James R.
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Electrical Engineering
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science
dc.format.digitalOrigin reformatted digital
dc.identifier.callno THESIS E.E. 1980 SWAMI
dc.identifier.citation Swami, Ananthram. "Estimation techniques in non-stationary renewal processes." (1980) Master’s Thesis, Rice University. https://hdl.handle.net/1911/104494.


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