Adaptive filtering and change detection

By Fredrik K. Gustafsson. 2000

1,192 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fa7353d6585fb3af672ac9154796221db04cb4e8

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Citations in the corpus

Kalman filter estimation of the number of competing terminals in an IEEE 802.11 network (2003, methodology): “In this paper, we have set the parameters h and v to be constant values; indeed, we recall that techniques are available [12] to”
Image change detection algorithms: a systematic survey (2005, background): “, [24]), and second, the video processing problem of determining the frame at which an image sequence switches between scenes (see, e.”
Identification of piecewise affine systems via mixed-integer programming (2004, background): “, [39]), is that the latter does not require linear separability between the classes; nor does it take the continuity of the PWA function into account.”
Cognitive radio: brain-empowered wireless communications (2005, methodology): “For a more refined approach, we may use an adaptive filter for change detection [42], [43].”
A Survey and Comparison of Time-Delay Estimation Methods in Linear Systems (2003, methodology): “See [Gus00] for estimating the change time when using CUSUM.”
A Survey of Fault Detection, Isolation, and Reconfiguration Methods (2010, methodology): “The book by Gustafsson [31] discusses both the theories of model-based filtering and change detection.”
Bibliographical review on reconfigurable fault-tolerant control systems (2003, unknown): “…books (Barron, 1996; Basseville & Benveniste, 1986; Basseville & Nikiforov, 1993; Chen & Patton, 1999; Chiang, Russell, & Braatz, 2001; Gertler, 1998; Gustafsson, 2000; Himmelblau, 1978; Isermann, 2006; Mangoubi, 1998; Natke & Cempel, 1997; Patton, Frank, & Clark, 1989, 2000; Pau, 1981; Pouliezos…”
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation (2012, background): “Though we estimated a density ratio between two consecutive segments, some earlier researches (Basseville and Nikiforov, 1993; Gustafsson, 1996, 2000) introduced a hyper-parameter that controls the size of a margin between two segments.”
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation (2009, background): “The conventional algorithms [5, 12] consider the likelihood ratio over samples from the two intervals.”
Ensemble learning for data stream analysis: A survey (2017, background): “On the other hand we do not want too many false alarms [70].”
Particle filters for positioning, navigation, and tracking (2002, background): “This is one of the key reasons for the success of the particle filter compared with other numerical approaches such as the point mass filter (a numerical integration technique that can be seen as a deterministic particle filter) [5] and filter banks [24].”
Particle methods for change detection, system identification, and control (2004, background): “The problems of model validation, change/fault detection, and isolation in dynamic models have received considerable attention; see, for example, [6] and [26].”