Fast orthogonal approximations of sampled sinusoids and bandlimited signals
Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin K. Romberg
Abstract
In this paper, we provide a dictionary for representing the discrete vector one obtains when collecting a finite set of uniform samples from a baseband analog signal. Like the discrete prolate spheroidal sequences (DPSS's), the proposed orthogonal basis compactly captures most of the energy in oversampled bandlimited signals. The complexity of computing the representation of a signal using the proposed dictionary is comparable to the FFT, which is much less than that involving the DPSS basis. We also give non-asymptotic results to guarantee that the proposed basis not only provides a very high degree of approximation accuracy in an MSE sense for bandlimited sample vectors, but also that it can provide high-quality approximations of all sampled sinusoids within the band of interest.
BibTeX
@inproceedings{icassp2017_fastorthogonalap,
title = {Fast orthogonal approximations of sampled sinusoids and bandlimited signals},
author = {Zhihui Zhu and Santhosh Karnik and Michael B. Wakin and Mark A. Davenport and Justin K. Romberg},
booktitle = {ICASSP 2017},
year = {2017}
}