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New prediction algorithms by covariance information based on innovation theory
Authors:S. Nakamori  A. Hataji
Affiliation:1. Department of Electrical Engineering, Oita University, Oita 870-11, Japan
Abstract:This paper states a new design method of recursive predictor and filter based on the innovations theory, using signal and noise covariance information, for white Gaussian and white Gaussian + coloured observation noises. The derived prediction and filtering algorithms estimate stationary stochastic signal processes.The digital simulation results indicate that the algorithms presented are feasible.
Keywords:Communications control applications  data processing  filtering  Markov processes  prediction  random processes  stochastic systems  time-domain analysis
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