Temporal and Spatial Functions | Teradata Vantage - Temporal and Spatial Functions - Teradata Vantage

Teradata® VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Vantage
Published
January 2023
Language
English (United States)
Last Update
2024-04-03
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The temporal and spatial functions allow you to perform spectral analysis of series or matrix datasets.

Functions:

TD_CONVOLVE
Applies digital filter to one-dimensional series by convolving time series with kernel filter.
TD_CONVOLVE2
Applies digital filter to a two-dimensional matrix by convolving time series with kernel filter.
TD_DFFT
Applies the Discrete Fast Fourier Transform to a one-dimensional series and returns a result series containing the computed Fourier Coefficients. The coefficients can be in rectangular (real, imaginary) or polar (amplitude, phase) form.
TD_DFFT2
Applies the Discrete Fast Fourier Transform to a two-dimensional array and returned a result matrix containing the computed two-dimension Fourier Coefficients. The coefficients can be in either rectangular (real, imaginary) or polar (amplitude, phase) form.
TD_DFFTCONV
Converts the Fourier Coefficient result series (ART), generated by TD_DFFT to either human-readable or raw forms, and in any of the supported rectangular and polar output formats.
TD_DFFT2CONV
Converts the Fourier Coefficient result matrixes (ART), generated by TD_DFFT2 to either human-readable or raw forms, and in any of the supported rectangular and polar output formats.
TD_GENSERIES4SINUSOIDS
Generates a result series containing a subset of the sinusoidal elements in the original input series.
TD_IDFFT
Reverses the effects of a Fourier transform on a one-dimensional series.
TD_IDFFT2
Reverses the effects of a Fourier transform on a two-dimensional matrix.
TD_LINESPEC
Uses a line spectrum function for identifying periodicities in time series.
TD_POWERSPEC
Uses a power spectrum function for estimating power spectrum associated with time series.