Journal of applied mathematics & informatics

  • 제8권3호
  • /
  • Pages.731-742
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  • 2001
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  • 2734-1194(pISSN)
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  • 2234-8417(eISSN)
한국전산응용수학회 (The Korean Society for Computational and Applied Mathematics)
권호 표지

A GAUSSIAN SMOOTHING ALGORITHM TO GENERATE TREND CURVES

  • 발행 : 2001.09.01

⟨ 이전 논문 다음 논문 ⟩

초록

A Gaussian smoothing algorithm obtained from a cascade of convolutions with a seven-point kernel is described. We prove that the change of local sums after applying our algorithm to sinusoidal signals is reduced to about two thirds of the change by the binomial coefficients. Hence, our seven point kernel is better than the binomial coefficients when trend curves are needed to be generated. We also prove that if our Gaussian convolution is applied to sinusoidal functions, the amplitude of higher frequencies reduces faster than the lower frequencies and hence that it is a low pass filter.

키워드

참고문헌

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  2. Computer Vision, Graphics, and Image Processing v.21 Fast algorithms for estimating local image properties P.J.Burt
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  5. Pattern Recognition Letters v.17 Automatic determination of the spread parameter in Gaussian smoothing H.C.Lin;L.L.Wang;S.N.Wang
  6. IEEE Trans. on Pattern Analysis and Machine Intelligence v.PAMI-8 no.1 Scale-based description and recognition of planar curves and two-dimensional shapes F.Mokhtarian;A.Mackworth
  7. Fuzzy Sets and systems v.96 A curve smoothing method by using fuzzy sets B.S.Moon
  8. An Introduction to Applied Probability Richard A. Roberts
  9. An Introduction to Wavelets Charles K. Chui
  10. The 4th Int. FLINS conf. on Intelligent Techniques and Soft Computing in Nuc. Sci. and Eng. Fuzzy Systems to Process ECG and EEG Signals for Quantification of the Mental Workload B.S.Moon(et al.)