In this paper, the eigenvalues and eigenvectors of the generalized discrete Fourier transform (GDFT), the generalized discrete Hartley transform (GDHT), the type-IV discrete cosine transform (DCT-IV), and the type-IV discrete sine transform (DST-IV) matrices are investigated in a unified framework. First, the eigenvalues and their multiplicities of the GDFT matrix are determined, and the theory of commuting matrices is applied to find the real, symmetric, orthogonal eigenvectors set that constitutes the discrete counterpart of Hermite Gaussian function. Then, the results of the GDFT matrix and the relationships among these four unitary transforms are used to find the eigenproperties of the GDHT, DCT-IV, and DST-IV matrices. Finally, the fractional versions of these four transforms are defined, and an image watermarking scheme is proposed to demonstrate the effectiveness of fractional transforms.

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

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

Abstract In this paper we present 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. A parallel algorithm is presented for one dimension Fourier transform with performance analysis. For a large array of complex numbers to be transformed, an almost linear speed-up is demonstrated. This algorithm can be executed by any number of processors, but generally the number is much less than the length of the input data.

A Parallel FFT on an MIMD Machine.

In this paper we present 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. A parallel algorithm is presented for one dimension Fourier transform with performance analysis. For a large array of complex numbers to be transformed, an almost linear speed-up is demonstrated. This algorithm can be executed by any number of processors, but generally the number is much less than the length of the input data.

A parallel FFT on an MIMD machine

Constant modulus transforms like discrete Fourier transform (DFT), Walsh transform, and Gold codes have been successfully used over several decades in several engineering applications, including discrete multi-tone (DMT), orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA) communications systems. In this paper, we present a generalized framework for DFT called Generalized DFT (GDFT) with nonlinear phase by exploiting the phase space. We show that GDFT offers sizable correlation improvements over DFT, Walsh, Oppermann and Gold codes, leading to better performance in all multi-carrier communications scenarios investigated. We also highlight how known constant modulus orthogonal transforms are special solutions of the proposed GDFT framework. Moreover, we introduce practical design methods offering computationally efficient implementations of GDFT as enhancements to DFT. We conclude the paper with examples of communications applications where GDFT is shown to outperform DFT and other known constant modulus bases.

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Generalized Discrete Fourier Transform With Nonlinear Phase

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.

Properties of the Multidimensional Generalized Discrete Fourier Transform

In this correspondence the problem of performing the multiplication by recoding the multiplier is considered. A special recoding for fractional numbers in two's complement form is presented, that generates a class of uniform shift multiplication algorithms having the property that every partial product is always in the open interval (-1,1). Both the scan of the multiplier from the least to the most significant bit and the scan in the opposite direction are considered.

Corsini

Papers

Properties of the Multidimensional Generalized Discrete Fourier Transform

Uniform Shift Multiplication Algorithms Without Overflow