Results 231 to 240 of about 1,797 (255)
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Nuclear norm minimization framework for DOA estimation in MIMO radar
Signal Processing, 2017In this paper, the direction of arrival (DOA) estimation for noncircular sources in multiple-input multiple-output (MIMO) radar is dealt with by a novel nuclear norm minimization (NNM) framework. The proposed method exploits the noncircular property of signals to extend the data model for doubling the array aperture.
Xianpeng Wang, Xiumei Li, Guoan Bi
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Rank constrained nuclear norm minimization with application to image denoising
Signal Processing, 2016In the low rank matrix approximation problem, the well known nuclear norm minimization (NNM) problem plays a crucial role and attracts significant interests in recent years. In NNM the regularization parameter λ plays a decisive part, λ controls both the rank of the solution and the extent of the thresholding.
Xixi Jia, Xiangchu Feng, Weiwei Wang
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Subspace identification for predictive state representation by nuclear norm minimization
2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), 2014Predictive State Representations (PSRs) are dynamical systems models that keep track of the system's state using predictions of future observations. In contrast to other models of dynamical systems, such as partially observable Markov decision processes, PSRs produces more compact models and can be consistently learned using statistics of the execution
Glaude, Hadrien +2 more
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Tight recovery thresholds and robustness analysis for nuclear norm minimization
2011 IEEE International Symposium on Information Theory Proceedings, 2011Nuclear norm minimization (NNM) has recently gained significant attention for its use in rank minimization problems. Using null space characterizations, recovery thresholds for NNM have been previously studied for the case of Gaussian measurements as matrix dimensions tend to infinity.
Oymak, Samet, Hassibi, Babak
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Event Recovery by Faster Truncated Nuclear Norm Minimization
2015When we want to know an event we are concerned, it is likely that the collected information is incomplete which may severely affect the consequent analysis. In this paper, we focus on the event recovery problem that aims to discover missing historical information for a certain event based on the limited known information. We formulate an event as a two
Debing Zhang +5 more
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Identification of power spectra by reweighted and regularized nuclear norm minimization
2015 10th Asian Control Conference (ASCC), 2015In this paper, we study model order choice in subspace identification algorithms using uniformly spaced spectrum measurements. In these algorithms, model order is determined by singular-value decomposition of a structured matrix constructed from spectrum measurements.
Hüseyin Akçay, Semiha Türkay
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Causal dynamic MRI reconstruction via nuclear norm minimization
Magnetic Resonance Imaging, 2012This work addresses the problem of online reconstruction of dynamic magnetic resonance images (MRI). The proposed method reconstructs the difference between the images of previous and current time frames. This difference image is modeled as a rank deficient matrix and is solved from the partially sampled k-space data via nuclear norm minimization.
Angshul, Majumdar, Rabab K, Ward
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Localization of Wireless Sensors via Nuclear Norm for Rank Minimization
2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010The low rank feature of location estimation in Wireless Sensor Networks (WSNs) makes it feasible to use nuclear norm minimization as an accurate and fast solution for low-dimensional embedding problems. In this paper, a novel localization algorithm for WSNs is proposed by using nuclear norm for rank minimization.
Chen Feng 0001 +3 more
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Patch Based Pansharpening Using Weighted Nuclear Norm Minimization
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019This paper proposed a multispectral (MS) and panchromatic (PAN) image fusion method based on low-rank assumption captured by weighted nuclear norm minimization (WNNM). In this method, low-rank matrix factorization is considered to model the relationship between low spatial resolution (LR) and high spatial resolution (HR) MS images.
Kai Zhang 0010, Feng Zhang 0028
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Nuclear norm minimization methods for frequency domain subspace identification
2012 American Control Conference (ACC), 2012ISBN:978-1-4577-1096 ...
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