Sampling and discretization of the linear canonical transform
Signal Processing
Generalized prolate spheroidal wave functions associated with linear canonical transform
IEEE Transactions on Signal Processing
Signal recovery with cost-constrained measurements
IEEE Transactions on Signal Processing
A fast algorithm for the linear canonical transform
Signal Processing
Speech recovery based on the linear canonical transform
Speech Communication
Multi-channel filter banks associated with linear canonical transform
Signal Processing
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We deal with the problem of efficient and accurate digital computation of the samples of the linear canonical transform (LCT) of a function, from the samples of the original function. Two approaches are presented and compared. The first is based on decomposition of the LCT into chirp multiplication, Fourier transformation, and scaling operations. The second is based on decomposition of the LCT into a fractional Fourier transform followed by scaling and chirp multiplication. Both algorithms take ~ N log N time, where N is the time-bandwidth product of the signals. The only essential deviation from exactness arises from the approximation of a continuous Fourier transform with the discrete Fourier transform. Thus, the algorithms compute LCTs with a performance similar to that of the fast Fourier transform algorithm in computing the Fourier transform, both in terms of speed and accuracy.