Predicting the statistical properties of least-squares polynomial filters

Experimental data generally consist of random noise superimposed on an unknown deterministic signal. Least-squares polynomial filters, introduced by Savitzky and Golay, are frequently used for reducing such noise in time-dependent data and for numerical differentiation

[1]  G. Petrucci,et al.  Studies of ultrasonic nebulizer parameters in search of a simple, reliable system , 1990 .

[2]  A. Khan.  Procedure for increasing the accuracy of the initial data point slope estimation by least-squares polynomial filters , 1988 .

[3]  W. J. Haas,et al.  Multielement detection limits and sample nebulization efficiencies of an improved ultrasonic nebulizer and a conventional pneumatic nebulizer in inductively coupled plasma-atomic emission spectrometry , 1977 .

[4]  Paul D. Willson,et al.  Digital Least Squares Smoothing of Spectra , 1974 .

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

[6]  A. Montaser,et al.  Versatile impedance matching network for inductively coupled plasma spectrometry , 1989 .

[7]  Joel M. Harris,et al.  Least-squares polynomial filters for initial point and slope estimation , 1984 .

[8]  R. J. Lang,et al.  Ultrasonic Atomization of Liquids , 1962 .

[9]  A. Montaser,et al.  Noise power spectra comparing He and Ar ICP discharges , 1989 .

[10]  S. R. Crouch,et al.  Frequency response of initial point least squares polynomial filters , 1987 .

[11]  Stephen E. Bialkowski,et al.  Generalized digital smoothing filters made easy by matrix calculations , 1989 .

[12]  G. Hieftje,et al.  An Efficient and Inexpensive Ultrasonic Nebulizer for Atomic Spectrometry , 1990 .

[13]  C. A. Barnardt,et al.  The role of desolvation and hydrogen addition on the excitation features of the inductively coupled plasma , 1988 .

[14]  V. Fassel,et al.  Induction-Coupled Plasma Spectrometric Excitation Source. , 1965 .

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

[16]  A. Montaser,et al.  Dual-beam, light-scattering interferometry for simultaneous measurements of droplet-size and velocity distributions of aerosols from commonly used nebulizers , 1990 .

[17]  A. Montaser,et al.  Atomic emission spectrometric detection limits and noise power spectra of argon inductively coupled plasma discharges formed with laminar- and tangential-flow torches , 1989 .

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

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

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

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

[22]  P. A. Baedecker,et al.  Comments on least-squares polynomial filters for initial point and slope estimation , 1985 .

[23]  V. Fassel,et al.  Ultrasonic nebulization of liquid samples for analytical inductively coupled plasma-atomic spectroscopy: an update , 1986 .

[24]  Stanley N. Deming,et al.  The use of linear models and matrix least squares in clinical chemistry. , 1979 .

[25]  D. N. Hume,et al.  Rapidfrequency Plasma Emission Spectrophotometer. , 1964 .

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

[27]  A. Proctor,et al.  Smoothing of digital x-ray photoelectron spectra by an extended sliding least-squares approach , 1980 .

[28]  C. Trassy,et al.  Inductively coupled plasma: the role of water in axial excitation temperatures , 1986 .