Extended Risk-sensitive Filter Based on Gaussian Process Regression
Author:
Affiliation:
1. Tokyo Metropolitan College of Industrial Technology
Publisher
The Society of Instrument and Control Engineers
Link
https://www.jstage.jst.go.jp/article/sicetr/54/2/54_253/_pdf
Reference12 articles.
1. 2) J. Ko and D. Fox: GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models, Autonomous Robots, 27-1, 75/90 (2009)
2. 3) C.M. Bishop: Pattern Recognition and Machine Learning, Springer (2006)
3. 4) J.L. Speyer, C.-H. Fan and R.N. Banavar: Optimal stochastic estimation with exponential cost criteria, IEEE Conference on Decision and Control, 2293/2298 (1992)
4. 5) B. Hassibi, A.H. Sayed and T. Kailath: Linear estimation in Krein spaces. II. Applications, IEEE Transactions on Automatic Control, 41-1, 34/49 (1996)
5. 6) M. Jayakumar and R.N. Banavar: Risk-Sensitive Filters for Recursive Estimation of Motion From Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, 20-6, 659/666 (1998)
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