@inproceedings{19fee1dd75a346639be26cf857f9ecc4,
title = "Linear prediction for bandpass signals based on nonuniform past samples",
abstract = "This paper concerns linear prediction of the value of a bandpass signal containing one or more passbands from a finite set of its past samples. The method of choosing prediction coefficients involves the eigenvector corresponding to the smallest eigenvalue of a matrix dependent on a function which is the Fourier transform of the set of intervals making up the passband. The method is developed for a set of arbitrary past samples and applied here to a set of «interlaced» samples that are nonuniform but periodic. The method applies to finite energy signals as well as to bandpass signals of polynomial growth, which connects to the theory of generalized functions. Computational examples are given of prediction coefficient values and of signal predictions.",
author = "Mugler, {Dale H.} and Yan Wu and Stuart Clary",
note = "Publisher Copyright: {\textcopyright} 2000 IEEE.; 25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 ; Conference date: 05-06-2000 Through 09-06-2000",
year = "2000",
doi = "10.1109/ICASSP.2000.860244",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3854--3857",
booktitle = "Design and Implementation of Signal Processing SystemNeural Networks for Signal Processing Signal Processing EducationOther Emerging Applications of Signal ProcessingSpecial Sessions",
address = "United States",
}