dc.contributor.author |
Arlı, A. Çağrı
|
|
dc.contributor.author |
Gazi, Orhan
|
|
dc.date.accessioned |
2022-06-17T12:18:00Z |
|
dc.date.available |
2022-06-17T12:18:00Z |
|
dc.date.issued |
2018 |
|
dc.identifier.citation |
Arlı, A. Çağrı; Gazi, Orhan (2018). "Mathematical modeling of stochastic resonance systems", 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, 2 May 2018 through 5 May 2018, pp. 1-4. |
tr_TR |
dc.identifier.isbn |
9781538615010 |
|
dc.identifier.uri |
http://hdl.handle.net/20.500.12416/5652 |
|
dc.description.abstract |
Knowledge of at which condition in a nonlinear threshold system stochastic resonance phenomena occurs, can be important in noise introduced threshold systems. A new method for mathematical modeling of stochastic resonance systems is introduced. The proposed approach can be used for the modeling of many other phenomenons. It's shown that using the mathematical model developed for stochastic resonance systems it's possible to estimate the optimum noise variances necessary for the occurrence of the stochastic resonance. The accuracy of the estimated noise variances are verified by the simulation results. © 2018 IEEE. |
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dc.language.iso |
eng |
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dc.relation.isversionof |
10.1109/SIU.2018.8404756 |
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dc.rights |
info:eu-repo/semantics/closedAccess |
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dc.subject |
Nonlinear Systems |
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dc.subject |
Stochastic Resonance |
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dc.subject |
Weak Signal Detection |
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dc.title |
Mathematical modeling of stochastic resonance systems |
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dc.title.alternative |
Stokastik rezonans sistemlerinin matematiksel modellenmesi |
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dc.type |
conferenceObject |
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dc.relation.journal |
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 |
tr_TR |
dc.contributor.authorID |
102896 |
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dc.identifier.startpage |
1 |
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dc.identifier.endpage |
4 |
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dc.contributor.department |
Çankaya Üniversitesi, Mühendislik Fakültesi, Elektronik ve Haberleşme Mühendisliği Bölümü |
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