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Diffusion estimation of state-space models: Bayesian formulation | IEEE Conference Publication | IEEE Xplore

Diffusion estimation of state-space models: Bayesian formulation


Abstract:

The paper studies the problem of decentralized distributed estimation of the state-space models from the Bayesian viewpoint. The adopted diffusion strategy, consisting of...Show More

Abstract:

The paper studies the problem of decentralized distributed estimation of the state-space models from the Bayesian viewpoint. The adopted diffusion strategy, consisting of collective adaptation to new data and combination of posterior estimates, is derived in general model-independent form. Its particular application to the celebrated Kalman filter demonstrates the ease of use, especially when the measurement model is rewritten into the exponential family form and a conjugate prior describes the estimated state.
Date of Conference: 21-24 September 2014
Date Added to IEEE Xplore: 20 November 2014
Electronic ISBN:978-1-4799-3694-6

ISSN Information:

Conference Location: Reims, France

References

References is not available for this document.