Analyzing large quantities of physical data during transient or other changing state conditions requires special treatment if results are to be useful. In this paper, results are derived for the accuracy to be associated with average response computations on a wide class of nonstationary data as a function of underlying signal and noise variations and the available sample size. Input and output signal-to-noise ratios are defined in terms of these quantities. Confidence bands are determined for both arbitrary probability distributions and for Gaussian probability distributions. A special result shows the increase in sample sizes required to analyze unknown distributions as opposed to Gaussian distributions in order to achieve a desired confidence band.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Methods for Analyzing Nonstationary Data


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Pre-1964 SAE Technical Papers ; 1906



    Publication date :

    1962-01-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English


    Keywords :