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# Each row of a matrix is then independently processed using a standard FFT algorithm.
The result (in natural order) is read column-by-column. Since the operations are performed column-wise and row-wise, step 2 and 4 (and reading the result) might include a matrix transposition to rearrange the elements in a way convenient for an FFT processing. The algorithm resembles a [[Multidimensional transform|2-dimensional FFT]], a 3-dimensional (and beyond) extensions are known as '''5-step FFT''', '''6-step FFT''', etc.{{sfn|Hart|Tornaría|Watkins|2010|p=191}}
The Bailey FFT is typically used for computing [[DFT]]s of large datasets, such as those used in scientific and engineering applications. The Bailey FFT is a very efficient algorithm, and it has been used to compute FFTs of datasets with billions{{fact}} of elements.
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