Abstract :
Continuous versions of the multidimensional chirp algorithms compute the function G(y)=F(My), where F(y) is the Fourier transform of a function f(x) of a vector variable x and M is an invertible matrix. Discrete versions of the algorithms compute values of F over the lattice L2=ML1 from values of f over a lattice L1, where L2 need not contain the lattice reciprocal to L1. If M is symmetric, the algorithms are multidimensional versions of the Bluestein chirp algorithm, which employs two pointwise multiplication operations (PMOs) and one convolution operation (CO). The discrete version may be efficiently implemented using fast algorithms to compute the convolutions. If M is not symmetric, three modifications are required. First, the Fourier transform is factored as the product of two Fresnel transforms. Second, the matrix M is factored as M=AB, where A and B are symmetric matrices. Third, the Fresnel transforms are modified by the matrices A and B and each modified transform is factored into a product of two PMOs and one CO
Keywords :
fast Fourier transforms; matrix algebra; vectors; Bluestein chirp algorithm; DFT; Fresnel transforms; M; convolution operation; discrete Fourier transform computation; fast algorithms; invertible matrix; multidimensional chirp algorithms; pointwise multiplication operations; symmetric matrices; Chirp; Convolution; Discrete Fourier transforms; Fourier transforms; Lattices; Matrix decomposition; Multidimensional systems; Signal processing algorithms; Symmetric matrices; Winches;