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arxiv: 1404.7713 · v2 · pith:UA67AMT4new · submitted 2014-04-30 · 🧮 math.CA · math.FA

On accumulated spectrograms

classification 🧮 math.CA math.FA
keywords omegadomaineigenfunctionsaccumulatedeigenvaluesspectrogramserrorspectrogram
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We study the eigenvalues and eigenfunctions of the time-frequency localization operator $H_\Omega$ on a domain $\Omega$ of the time-frequency plane. The eigenfunctions are the appropriate prolate spheroidal functions for an arbitrary domain $\Omega$. Indeed, in analogy to the classical theory of Landau-Slepian-Pollak, the number of eigenvalues of $H_\Omega$ in $[1-\delta , 1]$ is equal to the measure of $\Omega$ up to an error term depending on the perimeter of the boundary of $\Omega$. Our main results show that the spectrograms of the eigenfunctions corresponding to the large eigenvalues (which we call the accumulated spectrogram) form an approximate partition ofunity of the given domain $\Omega $. We derive both asymptotic, non-asymptotic, and weak $L^2$ error estimates for the accumulated spectrogram. As a consequence the domain $\Omega$ can be approximated solely from the spectrograms of eigenfunctions without information about their phase.

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