The paper provides a full self-contained derivation of fast algorithms to compute discrete Cosine and Sine transforms I IV. For the Sine I/II and Cosine I/II transforms a unified derivation based on the concept of the comrade matrix is presented. The comrade matrices associated with different versions of the transforms differ in only a few boundary elements; hence, in each case algorithms can b...

C06FKF Circular convolution or correlation of two real vectors, extra workspace for greater speed C06FPF Multiple one-dimensional real discrete Fourier transforms C06FQF Multiple one-dimensional Hermitian discrete Fourier transforms C06FRF Multiple one-dimensional complex discrete Fourier transforms C06FUF Two-dimensional complex discrete Fourier transform C06FXF Three-dimensional complex discr...

Fourier transform is an essential ingredient in Shor’s factoring algorithm. In the standard quantum circuit model with the gate set U 2 , controlled-NOT , the discrete Fourier transforms FN= ij N N, i , j=0,1 ,... ,N −1, =e2 i/N, can be realized exactly by quantum circuits of size O n2 , n=ln N, and so can the discrete sine or cosine transforms. In topological quantum computing, the simplest un...

A classical computer does not allow to calculate a discrete cosine transform on N points in less than linear time. This trivial lower bound is no longer valid for a computer that takes advantage of quantum mechanical superposition, entanglement, and interference principles. In fact, we show that it is possible to realize the discrete cosine transforms and the discrete sine transforms of size N ...

In this paper, the problem of blind separation of underdetermined noisy mixtures of audio sources is considered. The sources are assumed to be sparsely represented in a transform domain. The sparsity of their analysis coefficients is modelled by the Student t distribution. This prior allows for robust Bayesian estimation of the sources, the mixing matrix, the additive noise variance as well as ...

This paper is concerned with the definitions of the discrete fractional cosine transform (DFRCT) and the discrete fractional sine transform (DFRST). The definitions of DFRCT and DFRST are based on the eigen decomposition of DCT and DST kernels. This is the same idea as that of the discrete fractional Fourier transform (DFRFT); the eigenvalue and eigenvector relationships between the DFRCT, DFRS...

7 Trigonometric Identities, Complex Exponentials and Periodic Sequences 26 7.1 Basic Trigonometric Identities . . . . . . . . . . . . . . . . . . 26 7.2 Basic Trigonometric Integrals . . . . . . . . . . . . . . . . . . 28 7.3 Basic Properties of Complex Numbers . . . . . . . . . . . . . 29 7.4 Complex Numbers and Trigonometrical Identities . . . . . . . 31 7.5 The Exponential of a Complex Numbe...