A new statistical method for filtering and entropy estimation of a chaotic map from noisy data

G. Jogesh Babu; Abraham Boyarsky; Yogendra P. Chaubey; Pawel Góra

doi:10.1142/S0218127404011612

A new statistical method for filtering and entropy estimation of a chaotic map from noisy data

G. Jogesh Babu
, Abraham Boyarsky
, Yogendra P. Chaubey
, Pawel Góra

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We consider a discrete time deterministic chaotic dynamical system, x _n+1 = τ(x_n), where τ is a nonlinear map of the unit interval into itself. We assume that T is piecewise expanding and piecewise C². The effects of noise contamination are modeled by x _n+1 = τ(x_n) + ξ_n, where ξ_n is an independent random variable with small noise amplitude. A new statistical method is presented for filtering τ and estimating the metric entropy of τ from observed noisy data.

Original language	English (US)
Pages (from-to)	3989-3994
Number of pages	6
Journal	International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume	14
Issue number	11
DOIs	https://doi.org/10.1142/S0218127404011612
State	Published - Nov 2004

All Science Journal Classification (ASJC) codes

Modeling and Simulation
Engineering (miscellaneous)
General
Applied Mathematics

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10.1142/S0218127404011612

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abstract = "We consider a discrete time deterministic chaotic dynamical system, x n+1 = τ(xn), where τ is a nonlinear map of the unit interval into itself. We assume that T is piecewise expanding and piecewise C2. The effects of noise contamination are modeled by x n+1 = τ(xn) + ξn, where ξn is an independent random variable with small noise amplitude. A new statistical method is presented for filtering τ and estimating the metric entropy of τ from observed noisy data.",

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AU - Babu, G. Jogesh

AU - Boyarsky, Abraham

AU - Chaubey, Yogendra P.

AU - Góra, Pawel

PY - 2004/11

Y1 - 2004/11

N2 - We consider a discrete time deterministic chaotic dynamical system, x n+1 = τ(xn), where τ is a nonlinear map of the unit interval into itself. We assume that T is piecewise expanding and piecewise C2. The effects of noise contamination are modeled by x n+1 = τ(xn) + ξn, where ξn is an independent random variable with small noise amplitude. A new statistical method is presented for filtering τ and estimating the metric entropy of τ from observed noisy data.

AB - We consider a discrete time deterministic chaotic dynamical system, x n+1 = τ(xn), where τ is a nonlinear map of the unit interval into itself. We assume that T is piecewise expanding and piecewise C2. The effects of noise contamination are modeled by x n+1 = τ(xn) + ξn, where ξn is an independent random variable with small noise amplitude. A new statistical method is presented for filtering τ and estimating the metric entropy of τ from observed noisy data.

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U2 - 10.1142/S0218127404011612

DO - 10.1142/S0218127404011612

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JO - International Journal of Bifurcation and Chaos in Applied Sciences and Engineering

JF - International Journal of Bifurcation and Chaos in Applied Sciences and Engineering

IS - 11

ER -

A new statistical method for filtering and entropy estimation of a chaotic map from noisy data

Abstract

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