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Compression-Based Compressed Sensing [PDF]
IEEE Transactions on Information Theory, 2016 Modern compression algorithms exploit complex structures that are present in signals to describe them very efficiently. On the other hand, the field of compressed sensing is built upon the observation that "structured" signals can be recovered from their
Erkip, Elza +3 more
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Universal Compressed Sensing [PDF]
2016 IEEE International Symposium on Information Theory (ISIT), 2016 In this paper, the problem of developing universal algorithms for compressed sensing of stochastic processes is studied. First, R\'enyi's notion of information dimension (ID) is generalized to analog stationary processes.
Jalali, Shirin, Poor, H. Vincent
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Message-passing algorithms for compressed sensing [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2009 Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a known basis ...
David L. Donoho +2 more
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Sequential Compressed Sensing [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2009 Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sensing literature have focused on characterizing the achievable performance ...
Malioutov, Dmitry +2 more
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"Compressed" Compressed Sensing
2010 IEEE International Symposium on Information Theory, 2010 The field of compressed sensing has shown that a sparse but otherwise arbitrary vector can be recovered exactly from a small number of randomly constructed linear projections (or samples).
Gastpar, Michael, Reeves, Galen
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A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging [PDF]
Scientific Reports, 2017 Single-pixel imaging is an alternate imaging technique particularly well-suited to imaging modalities such as hyper-spectral imaging, depth mapping, 3D profiling.
Ming-Jie Sun +4 more
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Compressed Sensing for Biomedical Photoacoustic Imaging: A Review [PDF]
SensorsPhotoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging.
Yuanmao Wang +3 more
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Overview of Compressed Sensing: Sensing Model, Reconstruction Algorithm, and Its Applications
Applied Sciences, 2020 With the development of intelligent networks such as the Internet of Things, network scales are becoming increasingly larger, and network environments increasingly complex, which brings a great challenge to network communication.
Lixiang Li +5 more
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Compressive Sensing With Chaotic Sequence [PDF]
IEEE Signal Processing Letters, 2010 Compressive sensing is a new methodology to cap- ture signals at sub-Nyquist rate. To guarantee exact recovery from compressed measurements, one should choose specific matrix, which satisfies the Restricted Isometry Property (RIP), to implement the sensing procedure.
Lei Yu +3 more
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Algebraic compressed sensing [PDF]
Applied and Computational Harmonic Analysis, 2023 We introduce the broad subclass of algebraic compressed sensing problems, where structured signals are modeled either explicitly or implicitly via polynomials. This includes, for instance, low-rank matrix and tensor recovery. We employ powerful techniques from algebraic geometry to study well-posedness of sufficiently general compressed sensing ...
Breiding, Paul +3 more
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