IDWT2D (ML Engine) - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.10
1.1
Published
October 2019
Language
English (United States)
Last Update
2019-12-31
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

The IDWT2D function is the inverse of DWT2D (ML Engine); that is, IDWT2D applies inverse wavelet transforms on multiple sequences simultaneously. IDWT2D takes as input the output table and meta table output by DWT2D and outputs the sequences as 2-dimensional matrixes. (Because the IDWT2D output is comparable to the DWT2D input, the inverse transformation is also called the reconstruction.)


How Machine Learning Engine function IDWT2D works

This is a typical IDWT2D use case:

  1. Apply DWT2D to 2-dimensional sequences to create the coefficients of the matrixes and corresponding metadata.
  2. Filter the coefficients by methods appropriate for the objects (for example, minimum threshold or top n coefficients), compressing the original matrixes.
  3. Apply IDWT to the filtered coefficients to reconstruct the sequences.
  4. Compare the reconstructed matrixes to their original counterparts.