Sublinear-time algorithms for compressive phase retrieval

In the problem of compressed phase retrieval, the goal is to reconstruct a sparse or approximately k-sparse vector x in C n given access to y= |φ x|, where |v| denotes the vector obtained from taking the absolute value of v inCn coordinate-wise. In this paper we present sublinear-time algorithms for...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Li, Yi, Nakos, Vasileios
مؤلفون آخرون: School of Physical and Mathematical Sciences
التنسيق: مقال
اللغة:English
منشور في: 2022
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/161218
الوسوم: إضافة وسم
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الوصف
الملخص:In the problem of compressed phase retrieval, the goal is to reconstruct a sparse or approximately k-sparse vector x in C n given access to y= |φ x|, where |v| denotes the vector obtained from taking the absolute value of v inCn coordinate-wise. In this paper we present sublinear-time algorithms for a few for-each variants of the compressive phase retrieval problem which are akin to the variants considered for the classical compressive sensing problem in theoretical computer science. Our algorithms use pure combinatorial techniques and near-optimal number of measurements.