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Journal ArticleDOI

Properties of the Multidimensional Generalized Discrete Fourier Transform

Corsini, +1 more
- 01 Nov 1979 - 
- Vol. 28, Iss: 11, pp 819-830
TLDR
In this work the generalized discrete Fourier transform (GFT), which includes the DFT as a particular case, is considered, and two pairs of fast algorithms for evaluating a multidimensional GFT are given (T-algorithm, F-al algorithm, and T′-algorithms, F′-Algorithm).
Abstract
In this work the generalized discrete Fourier transform (GFT), which includes the DFT as a particular case, is considered. Two pairs of fast algorithms for evaluating a multidimensional GFT are given (T-algorithm, F-algorithm, and T′-algorithm, F′-algorithm). It is shown that in the case of the DFT of a vector, the T-algorithm represents a form of the classical FFT algorithm based on a decimation in time, and the F-algorithm represents a form of the classical FFT algorithm based on decimation in frequency. Moreover, it is shown that the T′-algorithm and the T-algorithm involve exactly the same arithmetic operations on the same data. The same property holds for the F′-algorithm and the F-algorithm. The relevance of such algorithms is discussed, and it is shown that the T′-algorithm and the F′-algorithm are particularly advantageous for evaluating the DFT of large sets of data.

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Citations
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Journal ArticleDOI

Eigenvalues and eigenvectors of generalized DFT, generalized DHT, DCT-IV and DST-IV matrices

TL;DR: The eigenvalues and eigenvectors of the generalized discrete Fourier transform, the GDHT, Hartley transform, DCT-IV, and DST-IV matrices, and the type-IV discrete sine transform matrices are investigated in a unified framework to demonstrate the effectiveness of fractional transforms.
Journal ArticleDOI

The fast generalized discrete Fourier transforms: a unified approach to the discrete sinusoidal transforms computation

TL;DR: The resulting generalized signal flow graphs for the computation of different versions of the GDFT represent simple and compact unified approach to the fast discrete sinusoidal transforms computation.
Proceedings Article

A Parallel FFT on an MIMD Machine.

TL;DR: In this paper, a parallel Cooley-Tukey FFT implementation on a shared-memory MIMD (non-vector) machine that was built in the Dept. of Computer Science, Tel Aviv University is presented.
Journal ArticleDOI

A parallel FFT on an MIMD machine

TL;DR: A parallelization of the Cooley- Tukey FFT algorithm that is implemented on a shared-memory MIMD (non-vector) machine that was built in the Dept. of Computer Science, Tel Aviv University is presented.
Journal ArticleDOI

Generalized Discrete Fourier Transform With Nonlinear Phase

TL;DR: A generalized framework for DFT called Generalized DFT (GDFT) with nonlinear phase by exploiting the phase space is presented, showing that GDFT offers sizable correlation improvements over DFT, Walsh, Oppermann and Gold codes, leading to better performance in all multi-carrier communications scenarios investigated.
References
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Journal ArticleDOI

An algorithm for the machine calculation of complex Fourier series

TL;DR: Good generalized these methods and gave elegant algorithms for which one class of applications is the calculation of Fourier series, applicable to certain problems in which one must multiply an N-vector by an N X N matrix which can be factored into m sparse matrices.
Proceedings ArticleDOI

Fast Fourier Transforms: for fun and profit

TL;DR: The "Fast Fourier Transform" has had a major effect on several areas of computing, the most striking example being techniques of numerical convolution, which have been completely revolutionized.
Journal ArticleDOI

A method for computing the fast Fourier transform with auxiliary memory and limited high-speed storage

TL;DR: An ALGOL procedure for computing the complex Fourier transform with four, six, or eight files is listed, and timing and accuracy test results are given.
Journal ArticleDOI

Parallelism in fast Fourier transform hardware

TL;DR: A diagrammatic representation of mixed radix and highest radix FFT algorithms is derived, and two broad classes of FFT hard-ware are explored, from the point of view of speed, parallelism, radix number, and type of memory.
Journal ArticleDOI

Fast Fourier transform of externally stored data

TL;DR: Two methods for FFT of one-dimensional arrays of data to be fast Fourier transformed are presented-one efficient when data storage is only slightly larger than available internal memory, and one when data is much larger.
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