Millimeter-accuracy Ultra-Wideband (UWB) positioning systems using the Time Difference Of Arrival (TDOA) algorithm are able to be utilized in military and many other important applications. Previous research on UWB positioning system has achieved up to mm or sub-mm accuracy. However, one bottleneck in UWB system is at sampling high resolution UWB signals, as well as high resolution timing infor...

Compressed Sensing MRI (CS-MRI) aims at reconstructing de-aliased images from sub-Nyquist sampling k-space data to accelerate MR Imaging, thus presenting two basic issues, i.e., where sample and how reconstruct. To deal with both problems simultaneously, we propose a novel end-to-end Probabilistic Under-sampling Explicable Reconstruction neTwork, dubbed PUERT, jointly optimize the...

Millimeter-accuracy Ultra-Wideband (UWB) positioning systems using the Time Difference Of Arrival (TDOA) algorithm are able to be utilized in military and many other important applications. Previous research on UWB positioning system has achieved up to mm or sub-mm accuracy. However, one bottleneck in UWB system is at sampling high resolution UWB signals, as well as high resolution timing infor...

We clarify the controversy over coherent-state (CS) versus number-state (NS) pictures in quantum optics. The NS picture is equivalent to the CS picture, as long as phase φ in laser fields are randomly distributed, as Mølmer argues. However, claim by Rudolph and Sanders [Phys. Rev. Lett. 87, 077903 (2001)] has a few gaps. First they make an assumption that is not necessarily true in calculation ...

Conventional compressive sampling (CS) primarily assumes light-tailed models for the underlying signal and/or noise statistics. Nevertheless, this assumption is abolished when operating in impulsive environments, where non-Gaussian infinite-variance processes arise components. This drives traditional linear operators to failure, since gross observation errors are spread uniformly over generated...

Introduction: Parallel imaging (PI) [1,2] is a well-established acceleration technique based on the spatial sensitivity of array receivers. Compressed sensing (CS) [3-5] is an emerging acceleration technique that is based on the compressibility of medical images. Attempts to combine [8-13] the two have been limited to straightforward extensions of SENSE [2] with SparseMRI [5]. Here we present a...

—To improve the speed of traditional signal sampling and processing, which is based on the Nyqusit-sampling theorem, a new theorem called Compressive Sensing (CS) is presented. Most work in CS has focused on reconstructing the high-bandwidth signals from nonuniform low-rate samples. However, the signal reconstruction process of CS needs large amount of computation. In this paper, under the fra...

1 Abstract—Phase modulation is a commonly used modulation mode in digital communication, which usually brings phase sparsity to digital signals. It is naturally to connect the sparsity with the newly emerged theory of compressed sensing (CS), which enables sub-Nyquist sampling of high-bandwidth to sparse signals. For the present, applications of CS theory in communication field mainly focus on ...

In the classical Shannon/Nyquist sampling theorem, information is not lost in uniformly sampling a signal, signal must be sampled at least two times faster than its bandwidth. Because of the restriction of the Nyquist rate, it end up with too many samples in many applications, and it becomes a great challenge for further transmission and storage. In recent years, an emerging theory of signal ac...