Union of low‐rank subspaces detector
نویسندگان
چکیده
منابع مشابه
A Union of Low-Rank Subspaces Detector
The problem of signal detection using a flexible and general model is considered. Due to applicability and flexibility of sparse signal representation and approximation, it has attracted a lot of attention in many signal processing areas. In this paper, we propose a new detection method based on sparse decomposition in a union of subspaces (UoS) model. Our proposed detector uses a dictionary th...
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We address the problem of recovering a high-dimensional but structured vector from linear observations in a general setting where the vector can come from an arbitrary union of subspaces. This setup includes well-studied problems such as compressive sensing and low-rank matrix recovery. We show how to design more efficient algorithms for the union-of-subspace recovery problem by using approxima...
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Traditional sampling theories consider the problem of reconstructing an unknown signal x from a series of samples. A prevalent assumption which often guarantees a unique signal consistent with the given measurements is that x lies in a known subspace. Recently, there has been growing interest in nonlinear but structured signal models, in which x is assumed to lie in a union of subspaces. An exa...
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As a generalization of the subspace fitting, the union of subspaces fitting problem consists in finding an union of subspaces in some given family that best fits to the finite data. This report provides a detailed review of the main reference [4] about the existence of such optimal solution. Proofs for a series of unproved statements in the reference are given. A basic background in topology an...
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Lower dimensional signal representation schemes frequently assume that the signal of interest lies in a single vector space. In the context of the recently developed theory of compressive sensing (CS), it is often assumed that the signal of interest is sparse in an orthonormal basis. However, in many practical applications, this requirement may be too restrictive. A generalization of the standa...
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ژورنال
عنوان ژورنال: IET Signal Processing
سال: 2016
ISSN: 1751-9675,1751-9683
DOI: 10.1049/iet-spr.2015.0009