Permuting streaming data using RAMs
Journal of the ACM (JACM)
Algebraic signal processing theory: Cooley-Tukey type algorithms for real DFTs
IEEE Transactions on Signal Processing
Conjugate symmetric sequency-ordered complex Hadamard transform
IEEE Transactions on Signal Processing
A general design for one dimensional discrete sine transform
Analog Integrated Circuits and Signal Processing
Algebraic signal processing theory: sampling for infinite and finite 1-D space
IEEE Transactions on Signal Processing
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This paper presents a systematic methodology to derive and classify fast algorithms for linear transforms. The approach is based on the algebraic signal processing theory. This means that the algorithms are not derived by manipulating the entries of transform matrices, but by a stepwise decomposition of the associated signal models, or polynomial algebras. This decomposition is based on two generic methods or algebraic principles that generalize the well-known Cooley-Tukey fast Fourier transform (FFT) and make the algorithms' derivations concise and transparent. Application to the 16 discrete cosine and sine transforms yields a large class of fast general radix algorithms, many of which have not been found before.