2002Unpublished venueRequires access

Exact finite dimensional filters for certain exponential functionals of Gaussian state space processes

Vikram Krishnamurthy, Robert J. Elliott

Open publisher page 2 citations

Abstract

In this paper, we derive finite dimensional filters for certain exponential functionals of the state of a continuous-time linear Gaussian process. Apart from being of mathematical interest, these new filters have applications in the state reconstruction of doubly-stochastic autoregressive processes. We also derive similar filters for exponential functionals of the state of nonlinear Benes systems.

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What this paper is about

In this paper, we derive finite dimensional filters for certain exponential functionals of the state of a continuous-time linear Gaussian process. Apart from being of mathematical interest, these new filters have applications in the state reconstruction of doubly-stochastic autoregressive processes. We also derive similar filters for exponential functionals of the state of nonlinear Benes systems.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper, we derive finite dimensional filters for certain exponential functionals of the state of a continuous-time linear Gaussian process. Apart from being of mathematical interest, these new filters have applications in the state reconstruction of doubly-stochastic autoregressive processes. We also derive similar filters for exponential functionals of the state of nonlinear Benes systems.

Key concepts: Exponential function, Gaussian, State space, Autoregressive model, Gaussian process, State (computer science), Mathematics, Applied mathematics

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