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AUTOMATICA
2005

Periodic signal analysis by maximum likelihood modeling of orbits of nonlinear ODEs

9 years 9 months ago
Periodic signal analysis by maximum likelihood modeling of orbits of nonlinear ODEs
This paper treats a new approach to the problem of periodic signal estimation. The idea is to model the periodic signal as a function of the state of a second-order nonlinear ordinary differential equation (ODE). This is motivated by Poincare theory, which is useful for proving the existence of periodic orbits for second-order ODEs. The functions of the right-hand side of the nonlinear ODE are then parameterized by a multivariate polynomial in the states, where each term is multiplied by an unknown parameter. A maximum likelihood algorithm is developed for estimation of the unknown parameters, from the measured periodic signal. The approach is analyzed by derivation and solution of a system of ODEs that describes the evolution of the Cramer
Torsten Söderström, Torbjörn Wigren
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where AUTOMATICA
Authors Torsten Söderström, Torbjörn Wigren, Emad Abd-Elrady
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