Least-squares polynomial filters for initial point and slope estimation

[1]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[2]  H. H. Madden.  Comments on the Savitzky-Golay convolution method for least-squares-fit smoothing and differentiation of digital data , 1976 .

[3]  C. G. Enke,et al.  Signal-to-Noise Ratio Enhancement by Least-Squares Polynomial Smoothing , 1976 .

[4]  J. Kaiser,et al.  Data smoothing using low‐pass digital filters , 1977 .

[5]  G. Horlick,et al.  Frequency response plots for Savitzky-Golay filter functions , 1977 .

[6]  D. Magde,et al.  Absolute quantum yield determination by thermal blooming. Fluorescein , 1978 .

[7]  M. Bromba,et al.  Efficient computation of polynomial smoothing digital filters , 1979 .

[8]  Horst Ziegler,et al.  Properties of Digital Smoothing Polynomial (DISPO) Filters , 1981 .

[9]  M. Bromba,et al.  Application hints for Savitzky-Golay digital smoothing filters , 1981 .

[10]  J. M. Harris,et al.  Comparison of single- and dual-beam configurations for thermal lens spectrometry , 1983 .

[11]  Horst Ziegler,et al.  Digital filter for computationally efficient smoothing of noisy spectra , 1983 .

[12]  Horst Ziegler,et al.  Digital smoothing of noisy spectra , 1983 .

[13]  P. Gans,et al.  Examination of the Convolution Method for Numerical Smoothing and Differentiation of Spectroscopic Data in Theory and in Practice , 1983 .

[14]  J. M. Harris,et al.  Supercritical fluids as spectroscopic solvents for thermooptical absorption measurements , 1984 .