Finding Representative Points of Closest Approach for Noisy Curves
Finding Representative Points of Closest Approach for Noisy Curves
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In our eReader you can find the full English version of the book. Read Finding Representative Points of Closest Approach for Noisy Curves Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book Finding Representative Points of Closest Approach for Noisy Curves
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244 0. 105 0. 097 0. 237 0. 210 0. 189 0. 263 0. 233 0. 286 Ce 9 1 2 1 3 2 3 0. 066 0. 061 0. 076 0. 064 0. 066 0. 049 0. 070 0. 074 0. 070 0. 146 0. 074 0. 077 0. 181 0. 160 0. 163 0. 229 0. 211 0. 259 Ce 15 1 2 1 3 2 3 0. 027 0. 028 0. 037 0. 030 0. 028 0. 024 0. 036 0. 031 0. 044 0. 050 0. 039 0. 063 0. 102 0. 097 0. 115 0. 178 0. 183 0. 229 Table 2 Quality of Matches The matches using quadratic approximations (coordinates vs arc length) are very bad, and in fact not useful, while using the ...cubic approximation to smooth noisy curves results in good matches when only a small section of the curve is used. As the amount of curve used in the fit is increased the quality of fit decreases, apparently because the location of points of closest approach of smooth curves is quite sensitive to slight changes of shape. The cubic fit procedure is superior to the centroid procedure when a small amount of the curves are used because, while the starting points for both procedures are the same, the fitting algorithm allows the representative point to move from the starting point more easily.
What to read after Finding Representative Points of Closest Approach for Noisy Curves?
You can find similar books in the "Read Also" column, or choose other free books by C Marc Bastuscheck to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
244 0. 105 0. 097 0. 237 0. 210 0. 189 0. 263 0. 233 0. 286 Ce 9 1 2 1 3 2 3 0. 066 0. 061 0. 076 0. 064 0. 066 0. 049 0. 070 0. 074 0. 070 0. 146 0. 074 0. 077 0. 181 0. 160 0. 163 0. 229 0. 211 0. 259 Ce 15 1 2 1 3 2 3 0. 027 0. 028 0. 037 0. 030 0. 028 0. 024 0. 036 0. 031 0. 044 0. 050 0. 039 0. 063 0. 102 0. 097 0. 115 0. 178 0. 183 0. 229 Table 2 Quality of Matches The matches using quadratic approximations (coordinates vs arc length) are very bad, and in fact not useful, while using the ...cubic approximation to smooth noisy curves results in good matches when only a small section of the curve is used. As the amount of curve used in the fit is increased the quality of fit decreases, apparently because the location of points of closest approach of smooth curves is quite sensitive to slight changes of shape. The cubic fit procedure is superior to the centroid procedure when a small amount of the curves are used because, while the starting points for both procedures are the same, the fitting algorithm allows the representative point to move from the starting point more easily.
What to read after Finding Representative Points of Closest Approach for Noisy Curves?
You can find similar books in the "Read Also" column, or choose other free books by C Marc Bastuscheck to read onlineMoreLess
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