Control adaptive for binary time series

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dc.contributor.authorAlması, Isaac
dc.contributor.authorJalilian, Reza
dc.date.accessioned2024-07-12T20:49:47Z
dc.date.available2024-07-12T20:49:47Z
dc.date.issued2009en_US
dc.departmentFakülteler, İnsan ve Toplum Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractThe model ARMAX provides a complete framework for stochastic difference equation. in this paper we will extend this methodology to cover binary time series. A particular example is the adaptive control of Markov processes with tow states. By employing a logistic model we will analyze a recursive estimator procedure and an adaptive control law. This enables the observer to regulate the transition probabilities system. These indicate that the proposed control law is asymptotically optimal with respect to a certain criterion. The paper terminates with illustrate some important points by simulations binary time series with inputs according a first order autoregressive process.en_US
dc.identifier.citationAlmasi, I. ve Jalilian, R. (2009). Control adaptive for binary time series. Maltepe Üniversitesi. s. 209.en_US
dc.identifier.endpage210en_US
dc.identifier.isbn9.78605E+12
dc.identifier.startpage209en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2232
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference of Mathematical Sciencesen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07559
dc.titleControl adaptive for binary time seriesen_US
dc.typeConference Object
dspace.entity.typePublication

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