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

M. Rahman

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 2, 289-306

Abstract: Matrix representation of a limit of variance for circular process is given. It is shown that the variance is asymptotically measured by the decrease in spectral energy in one step of a Markov chain. Then we apply this result to a stochastic differential equation with parametric noise (which arises in mathematical neuroscience) and demonstrate how the results can be used to analyze propagation of a signal in sound mechanism.

Date: 2018
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DOI: 10.1080/03610926.2017.1303729

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