Abstract

MEDEL, J.J  and  ZAGACETA, M. T.. State space second order filter estimation. Rev. mex. fis. [online]. 2013, vol.59, n.3, pp.254-257. ISSN 0035-001X.

The second order stochastic filter is based on difference models with uncorrelated innovation conditions structured in state space having stationary properties through a surface with bounded drift around the mean value. This allows building recursive estimation without generality lost and basic properties over the stochastic state space surface with unknown gains viewed as a black-box scheme. The spatial region generated gave an approximation to real parametres set with a sufficient convergence rate in a probability sense. The results were applied in adaptive identification states with a high convergence rate, observed in the functional error described illustratively in simulations. This technique was developed over the smooth slide surface having advantages over other traditional filters.

Keywords : State space estimation; least squares method; instrumental variable; second probability moment convergence rate.

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