1994
DOI: 10.1016/0010-4655(94)90228-3
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Adaptive projective filters for track finding

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Cited by 6 publications
(2 citation statements)
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“…This approach extends the framework of known classical methods and improves the quality and efˇciency of approximation algorithms. A number of methods and algorithms have been developed using DPT: the adaptive projectivě lters for trackˇnding [8]; DPT-function parametrization for uniform approximation over the whole interval [9]; polynomial approximation f (x) ∈ C (n) [a,b] , f (x) ∈ L 2 [9]. Comparison of DPT approximation with Chebyshev and Pade approximation has been done.…”
Section: Discussionmentioning
confidence: 99%
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“…This approach extends the framework of known classical methods and improves the quality and efˇciency of approximation algorithms. A number of methods and algorithms have been developed using DPT: the adaptive projectivě lters for trackˇnding [8]; DPT-function parametrization for uniform approximation over the whole interval [9]; polynomial approximation f (x) ∈ C (n) [a,b] , f (x) ∈ L 2 [9]. Comparison of DPT approximation with Chebyshev and Pade approximation has been done.…”
Section: Discussionmentioning
confidence: 99%
“…A polynomial with such properties can be constructed using 4-point transformations or DPT (Discrete Projective Transforms) that have been developed specially for these purposes [6,8,9]. It is necessary to note two essential moments in the structure of the polynomial model based on DPT.…”
Section: αβ-Parametrizationmentioning
confidence: 99%