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Volumn 17, Issue 8, 2010, Pages 707-710

The near constant acceleration gaussian process kernel for tracking

Author keywords

Bayesian methods; Gaussian processes; Kalman filter; near constant acceleration model; periodic dynamics; Target tracking

Indexed keywords

BAYESIAN METHODS; COMPLEX-PERIODIC; CONSTANT ACCELERATION; GAUSSIAN PROCESS MODELS; GAUSSIAN PROCESSES; GENERALISATION; MARKOV PROCESS MODEL; MOVING TARGETS; PERIODIC DYNAMICS; STANDARD KALMAN FILTERS; STATE-BASED; TIME SERIES PREDICTION;

EID: 77953989624     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2010.2051620     Document Type: Article
Times cited : (15)

References (10)
  • 5
    • 0003319647 scopus 로고    scopus 로고
    • Introduction to Gaussian processes
    • C.M. Bishop, Ed. Berlin, Germany: Springer-Verlag
    • D. J. C. Mackay, "Introduction to Gaussian processes," in Neural Netw. Mach. Learn., C. M. Bishop, Ed. Berlin, Germany: Springer-Verlag, 1998.
    • (1998) Neural Netw. Mach. Learn.
    • MacKay, D.J.C.1
  • 9
    • 77953980492 scopus 로고    scopus 로고
    • Prediction of estsp competition time series by unscented Kalman filter and rts smoother
    • Espoo, Finland
    • S. Särkkä, A. Vehtari, and J. Lampinen, "Prediction of estsp competition time series by unscented Kalman filter and rts smoother," in Proc. Eur. Symp. Time Series Prediction (ESTSP), Espoo, Finland, 2007.
    • (2007) Proc. Eur. Symp. Time Series Prediction (ESTSP)
    • Särkkä, S.1    Vehtari, A.2    Lampinen, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.