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• W2019371324 abstract "This paper is concerned with steady-state risk-sensitive filtering, prediction and smoothing problems for discrete-time singular systems. It is shown that a risk-sensitive estimator can be obtained by ensuring the minimum of an indefinite quadratic form to be maximum (minimum) when the risk-sensitivity parameter θ is negative (positive). An auxiliary state-space signal model and an innovation sequence in Krein space are introduced to simplify the derivation of the estimator. The estimator is calculated based on one J-spectral factorization for risk-seeking (θ<0) or one H2 spectral factorization for risk-averse (θ>0). A numerical example is given to demonstrate the applicability of the result." @default.
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• W2019371324 date "2003-01-01" @default.
• W2019371324 modified "2023-09-27" @default.
• W2019371324 title "Risk-sensitive filtering, prediction and smoothing for discrete-time singular systems" @default.
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• W2019371324 doi "https://doi.org/10.1016/s0005-1098(02)00168-1" @default.
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