A maximum likelihood estimation framework for the exponential Differential Equation Model | IEEE Conference Publication | IEEE Xplore

A maximum likelihood estimation framework for the exponential Differential Equation Model


Abstract:

In this paper we propose the maximum likelihood method of estimation for Delay Differential Equation Model governed by unknown delay and other parameters of interest. As ...Show More

Abstract:

In this paper we propose the maximum likelihood method of estimation for Delay Differential Equation Model governed by unknown delay and other parameters of interest. As an example we consider the Exponential Differential Equation Model. A grid based estimation framework is proposed. Our methodology estimates correctly the delay parameter as well as the initial starting value of the dynamical system based on simulation data.
Date of Conference: 05-07 October 2015
Date Added to IEEE Xplore: 11 January 2016
ISBN Information:
Conference Location: Bandung, Indonesia

I. Introduction

In biological models, time delays help to illustrate resource maturation periods, reaction times, feeding times, regeneration times, etc. [1]–[4]. Time delays disturb the stable equilibrium and cause a fluctuation in the population dynamics; hence Delay Differential Equations (DDEs) are generally more complex dynamic systems compared to Ordinary Differential Equations (ODEs). The parameters of Delay Differential Equation Models (DDEMs) are often unknown. Even though, a lot of the DDEM forms are proposed by investigators according to their grasp the underlying dynamical system.

References

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