NDLI: Generalized extended Kalman filter for prediction of chaotic time-series with intermittent failures

Content Provider	IEEE Xplore Digital Library
Author	Xuedong Wu Jin Huang Zhihuan Song
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. Inf.&Electr. Eng., Fujian Univ. of Technol., Fuzhou (Xuedong Wu; Jin Huang)
Abstract	There are many practical situations in which the chaotic signal appears in the observation in a random manner so that there are intermittent failures in the observation mechanism at certain times. Using weights and network output of neural network as state equation and observation equation to obtain the linear state transition equation, and the chaotic time-series prediction results represented by the predicted observation value, this paper generalizes the extended Kalman filter (EKF) to the case for the prediction of chaotic time-series with intermittent observations when random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables. Finally, we test this scheme using simulated data based on the generalized EKF with different Bernoulli distribution probability for uncertain observations. Simulation results of Lorenz time-series prediction with synthetic data prove that the proposed algorithm in this paper has satisfactory prediction precision as well as good robustness.
Starting Page	2355
Ending Page	2359
File Size	156844
Page Count	5
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4593291
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematical model Noise Equations Chaos Artificial neural networks Approximation methods Kalman filters Neural network approximation Uncertain observations Bernoulli multiplicative noise Chaotic time-series prediction Generalized Extended Kalman filtering
Content Type	Text
Resource Type	Article

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