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Volumn 79, Issue 6, 2009, Pages

Failures of sequential Bayesian filters and the successes of shadowing filters in tracking of nonlinear deterministic and stochastic systems

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN FILTERS; PARTICLE FILTER; SEQUENTIAL FILTER;

EID: 66049151122     PISSN: 15393755     EISSN: 15502376     Source Type: Journal    
DOI: 10.1103/PhysRevE.79.066206     Document Type: Article
Times cited : (21)

References (24)
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  • 19
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    • Consider a density p (x1, x2) zero everywhere, except on the set { (x1, x2) R2: x2 = x12 }, and is unimodal on this line with a maximum at (1, 1). The marginal density on x1 is unimodal with a maximum at x1 =1, but the marginal density on x2 can have two peaks at x2 =1 and x2 =0. Depending on how the density lies on the line, the peak at x2 =0 can be larger than the peak at x2 =1; hence, a marginal density can be misleading. Consequently, it is generally better to maximize a joint density to avoid this kind of situation.
    • Consider a density p (x1, x2) zero everywhere, except on the set { (x1, x2) R2: x2 = x12 }, and is unimodal on this line with a maximum at (1, 1). The marginal density on x1 is unimodal with a maximum at x1 =1, but the marginal density on x2 can have two peaks at x2 =1 and x2 =0. Depending on how the density lies on the line, the peak at x2 =0 can be larger than the peak at x2 =1; hence, a marginal density can be misleading. Consequently, it is generally better to maximize a joint density to avoid this kind of situation.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.