Linear estimation of continuous-discrete linear state space models with multiplicative noise

DOI10.1016/S0167-6911(02)00150-0zbMath1003.93046OpenAlexW1968968116MaRDI QIDQ1614846

J. C. Jimenez, Tohru Ozaki

Publication date: 9 September 2002

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-6911(02)00150-0

zbMATH Keywords

Kalman filtermultiplicative noisecontinuous-discrete state space modelslinear state space modelsoptimal minimum variance estimation

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10)

Related Items (12)

Simplified formulas for the mean and variance of linear stochastic differential equations ⋮ Local linearization filters for non-linear continuous-discrete state space models with multiplicative noise ⋮ A weak local linearization scheme for stochastic differential equations with multiplicative noise ⋮ Iterative linearization methods for approximately optimal control and estimation of non-linear stochastic system ⋮ Convergence rate of weak local linearization schemes for stochastic differential equations with additive noise ⋮ Computing multiple integrals involving matrix exponentials ⋮ The volatility structure of the fixed income market under the HJM framework: a nonlinear filtering approach ⋮ Derivation of linear estimation algorithms from measurements affected by multiplicative and additive noises ⋮ A state predictor for continuous-time stochastic systems ⋮ Variance decompositions of nonlinear time series using stochastic simulation and sensitivity analysis ⋮ Computing high dimensional multiple integrals involving matrix exponentials ⋮ An Approximate Innovation Method For The Estimation Of Diffusion Processes From Discrete Data

Uses Software

• Expokit

Cites Work

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