Quasi Monte Carlo time-frequency analysis

نویسندگان

چکیده

We study signal processing tasks in which the is mapped via some generalized time-frequency transform to a higher dimensional space, processed there, and synthesized an output signal. show how approximate such methods using quasi-Monte Carlo (QMC) approach. consider cases where representation redundant, having feature axes addition time frequency axes. The proposed QMC method allows sampling both efficiently evenly redundant representations. Indeed, 1) number of samples required for certain accuracy log-linear resolution depends only weakly on dimension 2) quasi-random have low discrepancy, so they are spread space. One example localizing (LTFT), plane enhanced by third axis. This space improves quality tasks, like phase vocoder (an audio effect). Since computational complexity this does not degrade computation method. more efficient than standard Monte methods, since deterministic sample points optimally while random not.

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ژورنال

عنوان ژورنال: Journal of Mathematical Analysis and Applications

سال: 2023

ISSN: ['0022-247X', '1096-0813']

DOI: https://doi.org/10.1016/j.jmaa.2022.126732