Combining H∞ filter and cost-reference particle filter for conditionally linear dynamic systems in unknown non-Gaussian noises-Reference-Cited by-同舟云学术

Combining H∞ filter and cost-reference particle filter for conditionally linear dynamic systems in unknown non-Gaussian noises

Published:2013-07 Issue:7 Volume:93 Page:1871-1878
ISSN:0165-1684
Container-title:Signal Processing
language:en
Short-container-title:Signal Processing

Author:

Yu Yihua

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software,Control and Systems Engineering

Reference25 articles.

1. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking;Arulampalam;IEEE Transactions on Signal Processing,2002

2. Deterministic resampling;Li;Signal Processing,2012

3. Mixture Kalman filters;Chen;Journal of the Royal Statistical Society Series B,2000

4. A. Doucet, J. de Freitas, K. Murphy, S. Russel, Rao-Blackwellized particle filtering for dynamic Bayesian networks, in: Proceedings of the Conference on Uncertainty in Artificial Intelligence, UAI, Stanford, CA, USA, 2000, pp. 176–183.

5. Marginalized particle filters for mixed linear/nonlinear state-space models;Schön;IEEE Transactions on Signal Processing,2005

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