The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform
S Boussakta - One of the best experts on this subject based on the ideXlab platform.
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fast walsh hadamard fourier Transform Algorithm
IEEE Transactions on Signal Processing, 2011Co-Authors: Mounir Taha Hamood, S BoussaktaAbstract:An efficient fast Walsh-Hadamard-Fourier Transform Algorithm which combines the calculation of the Walsh-Hadamard Transform (WHT) and the discrete Fourier Transform (DFT) is introduced. This can be used in Walsh-Hadamard precoded orthogonal frequency division multiplexing systems (WHT-OFDM) to increase speed and reduce the implementation cost. The Algorithm is developed through the sparse matrices factorization method using the Kronecker product technique, and implemented in an integrated butterfly structure. The proposed Algorithm has significantly lower arithmetic complexity, shorter delays and simpler indexing schemes than existing Algorithms based on the concatenation of the WHT and FFT, and saves about 70%-36% in computer run-time for Transform lengths of 16-4096.
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Fast Walsh–Hadamard–Fourier Transform Algorithm
IEEE Transactions on Signal Processing, 2011Co-Authors: Mounir Taha Hamood, S BoussaktaAbstract:An efficient fast Walsh-Hadamard-Fourier Transform Algorithm which combines the calculation of the Walsh-Hadamard Transform (WHT) and the discrete Fourier Transform (DFT) is introduced. This can be used in Walsh-Hadamard precoded orthogonal frequency division multiplexing systems (WHT-OFDM) to increase speed and reduce the implementation cost. The Algorithm is developed through the sparse matrices factorization method using the Kronecker product technique, and implemented in an integrated butterfly structure. The proposed Algorithm has significantly lower arithmetic complexity, shorter delays and simpler indexing schemes than existing Algorithms based on the concatenation of the WHT and FFT, and saves about 70%-36% in computer run-time for Transform lengths of 16-4096.
Mounir Taha Hamood - One of the best experts on this subject based on the ideXlab platform.
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fast walsh hadamard fourier Transform Algorithm
IEEE Transactions on Signal Processing, 2011Co-Authors: Mounir Taha Hamood, S BoussaktaAbstract:An efficient fast Walsh-Hadamard-Fourier Transform Algorithm which combines the calculation of the Walsh-Hadamard Transform (WHT) and the discrete Fourier Transform (DFT) is introduced. This can be used in Walsh-Hadamard precoded orthogonal frequency division multiplexing systems (WHT-OFDM) to increase speed and reduce the implementation cost. The Algorithm is developed through the sparse matrices factorization method using the Kronecker product technique, and implemented in an integrated butterfly structure. The proposed Algorithm has significantly lower arithmetic complexity, shorter delays and simpler indexing schemes than existing Algorithms based on the concatenation of the WHT and FFT, and saves about 70%-36% in computer run-time for Transform lengths of 16-4096.
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Fast Walsh–Hadamard–Fourier Transform Algorithm
IEEE Transactions on Signal Processing, 2011Co-Authors: Mounir Taha Hamood, S BoussaktaAbstract:An efficient fast Walsh-Hadamard-Fourier Transform Algorithm which combines the calculation of the Walsh-Hadamard Transform (WHT) and the discrete Fourier Transform (DFT) is introduced. This can be used in Walsh-Hadamard precoded orthogonal frequency division multiplexing systems (WHT-OFDM) to increase speed and reduce the implementation cost. The Algorithm is developed through the sparse matrices factorization method using the Kronecker product technique, and implemented in an integrated butterfly structure. The proposed Algorithm has significantly lower arithmetic complexity, shorter delays and simpler indexing schemes than existing Algorithms based on the concatenation of the WHT and FFT, and saves about 70%-36% in computer run-time for Transform lengths of 16-4096.
Z Wang - One of the best experts on this subject based on the ideXlab platform.
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A prime factor fast W Transform Algorithm
IEEE Transactions on Signal Processing, 1992Co-Authors: Z WangAbstract:A method for converting any nesting DFT Algorithm to the type-I discrete W Transform (DWT-I) is introduced. A nesting Algorithm that differs from either the Windograd Fourier Transform Algorithm (WFTA) or the prime factor FFT Algorithm (PFA) is presented. New small-N DETs, which are suitable for this nesting Algorithm, are developed based on using sparse matrix decomposition. The proposed Algorithm is more efficient that either WFTA or PFA for large N, and it is more flexible for the choice of Transform length, because 32 points are used. For 2D processing, the proposed Algorithm is more efficient than the polynomial Transform.
Harvey F. Silverman - One of the best experts on this subject based on the ideXlab platform.
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A method for programming the complex general-N Winograd Fourier Transform Algorithm
ICASSP '77. IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: Harvey F. SilvermanAbstract:The Winograd Fourier Transform Algorithm (WFTA) requires about 20% of the multiplications used in an optimized FFT, while the number of additions remains unchanged. This paper describes one "General-N" (i.e. many allowable DFT sizes (N) but certainly not any vector size) complex WFTA programming technique.
John G. Mcwhirter - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - A systolic implementation of the Winograd Fourier Transform Algorithm
ICASSP '85. IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: J. Ward, John V. Mccanny, John G. McwhirterAbstract:A bit-level systolic array system is proposed for the Winograd Fourier Transform Algorithm. The design uses bit-serial arithmetic and, in common with other systolic arrays, features nearest neighbour interconnections, regularity and high throughput. The short interconnections in this method contrast favourably with the long interconnections between butterflies required in the FFT. The structure is well suited to VLSI implementations. It is demonstrated how long Transforms can be implemented with components designed to perform short length Transforms. These components build into longer Transforms preserving the regularity and structure of the short length Transform design.
