搜索结果: 1-15 共查到“compressed sensing”相关记录21条 . 查询时间(0.109 秒)
The dynamics of message passing on dense graphs, with applications to compressed sensing
Mohsen Bayatil Andrea Montanari
2015/8/20
‘Approximate message passing’ algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive numerical experiments furthe...
CMOS Image Sensor With Per-Column ΣΔ ADC and Programmable Compressed Sensing
ΣΔ ADC CMOS image sensor compressed/compressive sensing
2015/8/12
A CMOS image sensor architecture with built-in single-shot compressed sensing is described. The image sensor employs a conventional 4-T pixel and per-column ΣΔ ADCs. The compressed sensing measurement...
Compressed sensing with quantized measurements
Signals gaussian noise interval value differentiable convex function
2015/8/7
We consider the problem of estimating a sparse signal from a set of quantized, Gaussian noise corrupted measurements, where each measurement corresponds to an interval of values. We give two methods f...
Compressed sensing based cone-beam computed tomography reconstruction with a first-order method
Department of Radiation Oncology Stanford University Stanford California 94305
2015/8/7
This article considers the problem of reconstructing cone-beam computed tomography (CBCT) images from a set of undersampled and potentially noisy projection measurements. The authors cast the reconstr...
We consider the problem of estimating a sparse signal from a set of quantized, Gaussian noise corrupted measurements, where each measurement corresponds to an interval of values. We give two methods f...
Compressed Sensing Based Cone-Beam Computed Tomography Reconstruction with a First-Order Method
cone-beam computed tomography compressed sensing weighted least-squares
2015/7/9
This article considers the problem of reconstructing cone-beam computed tomography (CBCT) images from a set of undersampled and potentially noisy projection measurements. The authors cast the reconstr...
The Restricted Isometry Property and Its Implications for Compressed Sensing
Restricted Isometry Property Compressed Sensing
2015/6/17
It is now well-known that one can reconstruct sparse or compressible signals accurately from a very limited number of measurements, possibly contaminated with noise. This technique known as “compresse...
We consider the problem of estimating a sparse signal from a set of quantized, Gaussian noise corrupted measurements, where each measurement corresponds to an interval of values. We give two methods f...
Compressed Sensing with Coherent and Redundant Dictionaries
Compressed Sensing Coherent and Redundant Dictionaries
2015/6/17
This article presents novel results concerning the recovery of signals from undersampled data in the common situation where such signals are not sparse in an orthonormal basis or incoherent dictionary...
A Compressed Sensing Parameter Extraction Platform for Radar Pulse Signal Acquisition
Compressed sensing Indium-Phosphide Parameter Estimation Random-Modulation Pre-Integration
2015/6/17
In this paper we present a complete (hardware/software) sub-Nyquist rate (×13) wideband signal acquisition chain capable of acquiring radar pulse parameters in an instantaneous bandwidth spanning 100 ...
Interference Cancellation in Wideband Receivers using Compressed Sensing
Compressed Sensing Interference cancellation wideband receivers LNA
2014/12/8
Previous approach for narrowband interference cancellation based on compressed sensing (CS) in wideband receivers uses orthogonal projections to project away from the interference. This is not effecti...
An analysis of block sampling strategies in compressed sensing
Compressed Sensing blocks of measurements sampling continuous trajectories exact recovery,ℓ 1 minimization.
2013/6/17
Compressed sensing (CS) is a theory which guarantees the exact recovery of sparse signals from a few number of linear projections. The sampling schemes suggested by current CS theories are often of li...
Compressed Sensing for Denoising in Adaptive System Identification
Sparse system identification compressed sensing reconstruction algorithm random filter least mean square
2012/4/23
We propose a new technique for adaptive identification of sparse systems based on the compressed sensing (CS) theory. We manipulate the transmitted pilot (input signal) and the received signal such th...
Efficient variational inference in large-scale Bayesian compressed sensing
large-scale Bayesian variational inference Computer Vision and Pattern Recognition
2011/10/9
Abstract: We study linear models under heavy-tailed priors from a probabilistic viewpoint. Instead of computing a single sparse most probable (MAP) solution as in standard deterministic approaches, th...
Weighted algorithms for compressed sensing and matrix completion
Compressed Sensing Weighted Basis-Pursuit Matrix Completion
2011/7/19
This paper is about iteratively reweighted basis-pursuit algorithms for compressed sensing and matrix completion problems. In a first part, we give a theoretical explanation of the fact that reweighte...