TD_DFFT Function | Teradata Vantage - TD_DFFT - Teradata Vantage

Database Unbounded Array Framework Time Series Functions

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Vantage
Release Number
17.20
Published
June 2022
Language
English (United States)
Last Update
2024-10-04
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TD_DFFT (Discrete Fast Fourier Transform) takes a time or space series as an input, and produces a result series containing the computed Fourier transform coefficients. The computed coefficients can be output in rectangular (real, imaginary) or polar (amplitude, phase) forms

The function is a version of the Fourier transform algorithm that is designed to handle discrete, finite-length signals. It is used in signal processing, image processing, audio signal processing, and telecommunications.

The DFFT algorithm operates on a sequence of N complex numbers, x[0], x[1], ..., x[N-1], and computes a corresponding sequence of N1 complex numbers, X[0], X[1], ..., X[N-1]. The DFFT algorithm has a computational complexity of 0(N log N), which makes it faster than the 0(N2) complexity of the naive DFT algorithm.

The TD_DFFT algorithm works by recursively parsing the input signal into smaller and smaller segments, and then combining the results to compute the final output. The algorithm takes advantage that a sequence can be expressed in terms of the Fourier transforms of its subsequences.

The following procedure is an example of how to use TD_DFFT when convolving two series with digital signal processing:
  1. Use TD_DFFT on series 1 and series 2 to get a tables named dfftRes1 and dfftRes2, respectively.
  2. Use TD_BINARYSERIESOP to do point-wise multiplication using dfftRes1 and dfftRes2, and name the resultant table freqRes.
  3. Use TD_IDFFT on freqRes to get the convolved result of the two series.