AN APPLICATION OF DECONVOLUTION OF CHAOTIC TIME SERIES DATA

Title of Publication: AN APPLICATION OF DECONVOLUTION OF CHAOTIC TIME SERIES DATA
Author(s): Agwuegbo S.O.N , Solarin A.R.T, Asiribo, O.E
Year of Publication: 2010
Abstract
Modeling and predicting the future evolution of a given time series from a chaotic dynamical system is one of the main tasks of nonlinear time series analysis. In this paper, attempts are made to build an appropriate model for the prediction of chaotic  time series by studying a dynamical system in its state space. The mathematical representation of the chaotic process, in this context, is by a set of linear stochastic differential equations with unique solutions. The first step is to reduce the complexity of the phenomenon by breaking it up into pieces all of which can be treated as independent of each other. The second guiding principle is to look for invariance’s, in time or space or with respect to transformations of the phenomenon, which leave the probabilities of the system unchanged.  For simplification,   individual risks policies suggestive enough to demonstrate relevance of the method in more realistic insurance models was illustrated in simple context so that the basic ideas can be easily grasped.

Keywords: Dynamics, Random Differential Equation,Insurance Claim, Chaos, Brownian Motion

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