Results 31 to 40 of about 66,013 (262)
Deep Unfolded Gridless DOA Estimation Networks Based on Atomic Norm Minimization
Remote Sensing, 2022 Deep unfolded networks have recently been regarded as an essential way to direction of arrival (DOA) estimation due to the fast convergence speed and high interpretability. However, few consider gridless DOA estimation.
Hangui Zhu +4 more
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Sparse Recovery with Very Sparse Compressed Counting
CoRR, 2013 Compressed sensing (sparse signal recovery) often encounters nonnegative data (e.g., images). Recently we developed the methodology of using (dense) Compressed Counting for recovering nonnegative K-sparse signals. In this paper, we adopt very sparse Compressed Counting for nonnegative signal recovery.
Ping Li 0001 +2 more
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Sparse System Identification of Leptin Dynamics in Women With Obesity
Frontiers in Endocrinology, 2022 The prevalence of obesity is increasing around the world at an alarming rate. The interplay of the hormone leptin with the hypothalamus-pituitary-adrenal axis plays an important role in regulating energy balance, thereby contributing to obesity.
Md. Rafiul Amin +5 more
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Continuous-Time Sparse Signal Recovery
IEEE AccessThis study investigates a continuous-time method for sparse signal recovery, which is suitable for analog optical circuit implementation. The proposed method is defined by a nonlinear ordinary differential equation (ODE) derived from the gradient flow ...
Tadashi Wadayama, Ayano Nakai-Kasai
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Jointly Iterative Adaptive Approach Based Space Time Adaptive Processing Using MIMO Radar
IEEE Access, 2018 To solve the problem of large training samples requirement of space time adaptive processing (STAP), a jointly sparse matrices recovery-based method is proposed for clutter plus noise covariance matrix estimation by exploiting the transmitting waveform ...
Weike Feng +4 more
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Jump-Sparse and Sparse Recovery Using Potts Functionals [PDF]
IEEE Transactions on Signal Processing, 2014 We recover jump-sparse and sparse signals from blurred incomplete data corrupted by (possibly non-Gaussian) noise using inverse Potts energy functionals. We obtain analytical results (existence of minimizers, complexity) on inverse Potts functionals and provide relations to sparsity problems.
Martin Storath +2 more
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New Sufficient Conditions of Signal Recovery With Tight Frames via
IEEE Access, 2018 This paper discusses the recovery of signals that are nearly sparse with respect to a tight frame D by means of the l1-analysis approach. We establish several new sufficient conditions regarding the D-restricted isometry property to ensure stable ...
Jianwen Huang +3 more
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Three-Dimensional Imaging of Terahertz Circular SAR with Sparse Linear Array
Sensors, 2018 Due to the non-contact detection ability of radar and the harmlessness of terahertz waves to the human body, three-dimensional (3D) imaging using terahertz synthetic aperture radar (SAR) is an efficient method of security detection in public areas.
Jubo Hao, Jin Li, Yiming Pi
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An asynchronous parallel approach to sparse recovery [PDF]
2017 Information Theory and Applications Workshop (ITA), 2017 5 pages, 2 ...
Deanna Needell, Tina Woolf
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Uncertainty Relations and Sparse Signal Recovery [PDF]
, 2021 Chapter in Information-theoretic Methods in Data Science, M. Rodrigues and Y.
Erwin Riegler, Helmut Bölcskei
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