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	<title>2018Boumal SinglePass - Revision history</title>
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	<updated>2026-06-13T12:13:45Z</updated>
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		<title>WikiSysop: Created page with &quot;== Citation ==  Boumal, N.; Bendory, T.; Lederman, R. R. &amp; Singer, A. Heterogeneous multireference alignment: A single pass approach. Proc. 52nd Annual Conf. Information Scien...&quot;</title>
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		<updated>2019-04-16T05:49:04Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== Citation ==  Boumal, N.; Bendory, T.; Lederman, R. R. &amp;amp; Singer, A. Heterogeneous multireference alignment: A single pass approach. Proc. 52nd Annual Conf. Information Scien...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== Citation ==&lt;br /&gt;
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Boumal, N.; Bendory, T.; Lederman, R. R. &amp;amp; Singer, A. Heterogeneous multireference alignment: A single pass approach. Proc. 52nd Annual Conf. Information Sciences and Systems (CISS), 2018, 1-6&lt;br /&gt;
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== Abstract ==&lt;br /&gt;
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Multireference alignment (MRA) is the problem of estimating a signal from many noisy and cyclically shifted copies of itself. In this paper, we consider an extension called heterogeneous MRA, where K signals must be estimated, and each observation comes from one of those signals, unknown to us. This is a simplified model for the heterogeneity problem notably arising in cryo-electron microscopy. We propose an algorithm which estimates the K signals without estimating either the shifts or the classes of the observations. It requires only one pass over the data and is based on low-order moments that are invariant under cyclic shifts. Given sufficiently many measurements, one can estimate these invariant features averaged over the K signals. We then design a smooth, non-convex optimization problem to compute a set of signals which are consistent with the estimated averaged features. We find that, in many cases, the proposed approach estimates the set of signals accurately despite non-convexity, and conjecture the number of signals K that can be resolved as a function of the signal length L is on the order of √L.&lt;br /&gt;
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== Keywords ==&lt;br /&gt;
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== Links ==&lt;br /&gt;
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https://ieeexplore.ieee.org/abstract/document/8362313&lt;br /&gt;
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== Related software ==&lt;br /&gt;
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== Related methods ==&lt;br /&gt;
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== Comments ==&lt;/div&gt;</summary>
		<author><name>WikiSysop</name></author>
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