Numerical Smoothing and Differentiation

Numerical Smoothing And Differentiation

An experimental datum value can be conceptually described as the sum of a signal and some noise, but in practice the two contributions cannot be separated. The purpose of smoothing is to increase the signal-to-noise ratio without greatly distorting the signal (i.e. to get rid of the noise). One way to achieve this is by fitting successive sets of m data points to a polynomial of degree less than m by the method of linear least squares. Once the coefficients of the smoothing polynomial have been calculated they can be used to give estimates of the signal or its derivatives.

Read more about Numerical Smoothing And Differentiation:  Convolution Coefficients, Signal Distortion and Noise Reduction, Frequency Characteristics of Convolution Filters, Convolution and Correlation, Two-dimensional Convolution Coefficients, Applications, See Also

Famous quotes containing the words numerical and/or smoothing:

    The terrible tabulation of the French statists brings every piece of whim and humor to be reducible also to exact numerical ratios. If one man in twenty thousand, or in thirty thousand, eats shoes, or marries his grandmother, then, in every twenty thousand, or thirty thousand, is found one man who eats shoes, or marries his grandmother.
    Ralph Waldo Emerson (1803–1882)

    Whale on the beach, you dinosaur,
    what brought you smoothing into this dead harbor?
    If you’d stayed inside you could have grown
    as big as the Empire State.
    Anne Sexton (1928–1974)