We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Fast computation of real discrete Fourier transform for any number of data points

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hu, N.-C. ; Nat. Taiwan Inst. of Technol., Taipei, Taiwan ; Ersoy, O.K.

In many applications, it is desirable to have a fast algorithm (RFFT) for the computation of the real discrete Fourier transform (RDFT) for any number of data points N. To achieve this, the two-factor Cooley-Tukey decimation-in-time and decimation-in-frequency RFFT algorithms are first developed and expressed in terms of matrix factorization using Kronecker products. This is generalized to any number of factors with arbitrary radices. Each factor M involves the computation of the size-M RDFT, which is carried out by the best size-M RFFT algorithm available. The RFFT algorithm for the case where M is a prime number is also developed. The RFFT algorithms are more efficient in the number of operations when the factors are arranged in a certain order, unlike the Cooley-Tukey complex FFT algorithms. which have the same number of operations for any order of the factors

Published in:

Circuits and Systems, IEEE Transactions on  (Volume:38 ,  Issue: 11 )