Asymptotic estimate of variance with applications to stochastic differential equations arises in mathematical neuroscience

DOI10.1080/03610926.2017.1303729zbMath1386.60244OpenAlexW2594943225MaRDI QIDQ4638706

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Publication date: 27 April 2018

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://digitalcommons.unf.edu/cgi/viewcontent.cgi?article=1034&context=facultyshowcase

zbMATH Keywords

variancechaincircular Markov processtheta-dot networkvoltage control oscillator

Mathematics Subject Classification ID

Discrete-time Markov processes on general state spaces (60J05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Neural networks for/in biological studies, artificial life and related topics (92B20) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35)

Cites Work

• Stochastic approximations of perturbed Fredholm Volterra integro-differential equation arising in mathematical neurosciences
• Random perturbation methods with applications in science and engineering
• Synaptic organizations and dynamical properties of weakly connected neural oscillators. I: Analysis of a canonical model
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