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- W2912140976 abstract "This chapter details the basic operations required to estimate various properties of random data. Special operations of common interest for data preparation include (a) data standardization, (b) trend removal, and (c) digital filtering. Fourier series and Fourier transforms of data differ in their theoretical properties but not in their digital computational details. One of the main reasons for the importance of fast Fourier transforms is that they can be used to provide estimates of desired spectral density and correlation functions. There are two ways to compute autocorrelation estimates. The first is the direct method, involving the computation of average products among the sample data values. The second way is the indirect approach of first computing an autospectral density estimate using fast Fourier transform (FFT) procedures and then computing the inverse transform of the autospectrum. The chapter lists iterative algebraic procedures to solve multiple-input/single-output problems. Controlled Vocabulary Terms autocorrelation function; data analysis; fast Fourier transform; input/output process; probability density function" @default.
- W2912140976 created "2019-02-21" @default.
- W2912140976 date "2010-01-21" @default.
- W2912140976 modified "2023-09-26" @default.
- W2912140976 title "Data Analysis" @default.
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- W2912140976 doi "https://doi.org/10.1002/9781118032428.ch11" @default.
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