arXiv subjects

Chen Wang

Publications and source records attributed to Chen Wang.

At least 721 records · Page 40Linked to original sources

arXiv2020

Deep-learning-based optical image hiding

A novel framework of optical image hiding based on deep learning (DL) is proposed in this paper, and hidden information can be reconstructed from an interferogram by using an end to end network with high-quality. By using the prior data between the hidden image and the object image, a generative adversarial network was trained so that it can learn the hiding model, which resulting in only an interferogram needs to be transmitted and recorded to reconstruct image. Moreover, reconstruction process can be obtained without the parameters in optical inverse diffraction and the reconstruction result will not be affected by the phase shifts deviation and noise, which is convenient for practical application. The feasibility and security of the proposed method are demonstrated by the optical experiment results.

eess.IV↗

arXiv2020

Divisibility results concerning truncated hypergeometric series

In this paper, using the well-known Karlsson-Minton formula, we mainly establish two divisibility results concerning truncated hypergeometric series. Let $n>2$ and $q>0$ be integers with $2\mid n$ or $2\nmid q$. We show that $$\sum_{k=0}^{p-1}\frac{(q-\frac{p}{n})_k^n}{(1)_k^n}\equiv0\pmod{p^3} $$ and $$p^n\sum_{k=0}^{p-1}\frac{(1)_k^n}{(\frac{p}{n}-q+2)_k^n}\equiv0\pmod{p^3}$$ for any prime $p>\max\{n,(q-1)n+1\}$, where $(x)_k$ denotes the Pochhammer symbol defined by $$ (x)_k=\begin{cases}1,\quad &k=0,\\ x(x+1)\cdots(x+k-1),\quad &k>0.\end{cases}$$ Let $n\geq4$ be an even integer. Then for any prime $p$ with $p\equiv-1\pmod{n}$, the first congruence above implies that $$\sum_{k=0}^{p-1} \frac{(\frac{1}{n})_k^n}{(1)_k^n}\equiv0\pmod{p^3}. $$ This confirms a recent conjecture of Guo.

math.NT↗

arXiv2020

Towards Critical Clearing Time Sensitivity for DAE Systems with Singularity

Standard power system models are parameter dependent differential-algebraic equation (DAE) type. Following a transient event, voltage collapse can occur as a bifurcation of the transient load flow solutions which is marked by the system trajectory reaching a singular surface in state space where the voltage causality is lost. If a fault is expected to cause voltage collapse, preventive control decisions such as changes in AVR settings need to be taken in order to get enhance the system stability. In this regard, the knowledge of sensitivity of critical clearing time (CCT) to controllable system parameters can be of great help. The quasi-stability boundary of DAE systems is more complicated than ODE systems where in addition to unstable equilibrium points (UEP) and periodic orbits, singularity plays an important role making the problem challenging. The stability boundary is then made up of a number of dynamically distinct components. In the present work, we derive the expression for CCT sensitivity for the phenomenon where the critical fault-on trajectory intersects the singular surface itself which is one such component forming the stability boundary. The results are illustrated for a small test system in order to gain visual insights.

eess.SY↗

arXiv2020

Optical Vortex Shaping & Multiple Singularities Manipulation via High-order Cross-phase

Increasing demand for practical applications is forcing deeper research into optical vortices (OVs): from the generation and measurement to shaping and multiple singularities manipulation of OVs. Herein, we propose a new type of phase structure called the high-order cross phase (HOCP) can be employed to modulate OVs to implement both polygonal shaping and singularities manipulation. Theoretically, we investigate the propagation characteristics of OVs with the HOCP. In experiments, we achieve the shaping and singularities manipulation of OVs by utilizing the HOCP. On this basis, we discuss the interference patterns of superposed OVs after the modulation. This work provides an alternative method to achieve both polygonal shaping and multiple singularities manipulation, which will facilitate applications in optical micro-manipulation, optical communication, and high-dimensional quantum entanglement.

physics.optics↗

arXiv2020

Low Voltage Ride Through (LVRT) Constrained Transient Stability Assessment Using Lyapunov Functions Family Method

Growing penetration of renewable generation in power systems brings more challenges in transient stability assessment using direct methods. One of the reasons is the inability to assess the risk of instability brought by tripping of a large amount of RGs due to violation of their ride through curves. In this paper, a scalable approach is proposed based on the Lyapunov functions family to estimate the stability region under ride through constraints. An inner polytopic approximation to the feasibility region is proposed to convexify the overall problem. The acquired constrained stability region estimate helps capture trajectories that trigger undesirable tripping of renewable generation. A 2-machine system is used to visualize its effectiveness.

eess.SY↗

arXiv2020

In-orbit Calibration to the Point-Spread Function of Insight-HXMT

We make the in-orbit calibration to the point-spread functions (PSFs) of the collimators of the Hard X-ray Modulation Telescope with the scanning observation of the Crab. We construct the empirical adjustments to the theoretically calculated geometrical PSFs. The adjustments contain two parts: a rotating matrix to adjust the directional deviation of the collimators and a paraboloidal function to correct the inhomogeneity of the real PSFs. The parameters of the adjusting matrices and paraboloidal functions are determined by fitting the scanning data with lower scanning speed and smaller intervals during the calibration observations. After the PSF calibration, the systematic errors in source localization in the Galactic plane scanning survey are 0.010 deg, 0.015 deg, 0.113 deg for the Low-Energy Telescope (LE), the Medium-Energy telescope (ME) and the High-Energy telescope (HE), respectively; meanwhile, the systematic errors in source flux estimation are 1.8%, 1.6%, 2.7% for LE, ME and HE, respectively.

astro-ph.IM↗

arXiv2020

Adaptive LVRT Settings Adjustment for Enhancing Voltage Security of Renewable-Rich Electric Grids

Inverter based renewable generation (RG), especially at the distribution level, is supposed to trip offline during an islanding situation. However, islanding detection is done by comparing the voltage and frequency measurements at the point of common coupling (PCC), with limits defined in the form of ride-through curves. Current practice is to use the same limit throughout the year independent of the operating conditions. This could result in the tripping of RG at times when the system is already weak, thereby posing a threat to voltage security by heavily limiting the load margin (LM). Conversely, heavily relaxing these limits would result in scenarios where the generation does not go offline even during an islanding situation. The proposed methodology focuses on optimizing low-voltage ride-through (LVRT) settings at selective RGs as a preventive control for maintaining a desired steady-state voltage stability margin while not sacrificing dependability during islanding. The proposed process is a multi-stage approach, in which at each stage, a subset of estimated poor-quality solutions is screened out based on various sensitivities. A full continuation power flow (CPFLOW) is only run at the beginning and in the last stage on a handful of remaining candidate solutions, thereby cutting down heavily on the computation time. The effectiveness of the approach is demonstrated on the IEEE 9-bus system.

eess.SY↗

arXiv2020

On a conjectural congruence of Guo

Let $p\equiv3\pmod{4}$ be a prime and $r$ a positive integer. We show that $$ \prod_{k=1}^{(p^{2r}-1)/2}\frac{4k-1}{4k+1}\equiv1\pmod{p^2}. $$ This confirms a recent conjecture of Guo.

math.NT↗

arXiv2020

Cooperative Pursuit with Multi-Pursuer and One Faster Free-moving Evader

This paper addresses a multi-pursuer single-evader pursuit-evasion game where the free-moving evader moves faster than the pursuers. Most of the existing works impose constraints on the faster evader such as limited moving area and moving direction. When the faster evader is allowed to move freely without any constraint, the main issues are how to form an encirclement to trap the evader into the capture domain, how to balance between forming an encirclement and approaching the faster evader, and what conditions make the capture possible. In this paper, a distributed pursuit algorithm is proposed to enable pursuers to form an encirclement and approach the faster evader. An algorithm that balances between forming an encirclement and approaching the faster evader is proposed. Moreover, sufficient capture conditions are derived based on the initial spatial distribution and the speed ratios of the pursuers and the evader. Simulation and experimental results on ground robots validate the effectiveness and practicability of the proposed method.

eess.SY↗

arXiv2020

Graph Optimization Approach to Range-based Localization

In this paper, we propose a general graph optimization based framework for localization, which can accommodate different types of measurements with varying measurement time intervals. Special emphasis will be on range-based localization. Range and trajectory smoothness constraints are constructed in a position graph, then the robot trajectory over a sliding window is estimated by a graph based optimization algorithm. Moreover, convergence analysis of the algorithm is provided, and the effects of the number of iterations and window size in the optimization on the localization accuracy are analyzed. Extensive experiments on quadcopter under a variety of scenarios verify the effectiveness of the proposed algorithm and demonstrate a much higher localization accuracy than the existing range-based localization methods, especially in the altitude direction.

cs.RO↗

arXiv2020

Kervolutional Neural Networks

Convolutional neural networks (CNNs) have enabled the state-of-the-art performance in many computer vision tasks. However, little effort has been devoted to establishing convolution in non-linear space. Existing works mainly leverage on the activation layers, which can only provide point-wise non-linearity. To solve this problem, a new operation, kervolution (kernel convolution), is introduced to approximate complex behaviors of human perception systems leveraging on the kernel trick. It generalizes convolution, enhances the model capacity, and captures higher order interactions of features, via patch-wise kernel functions, but without introducing additional parameters. Extensive experiments show that kervolutional neural networks (KNN) achieve higher accuracy and faster convergence than baseline CNN.

cs.CV↗

arXiv2020

Effects of close binary evolution on the main-sequence morphology of young star clusters

Star clusters are the building blocks of galaxies. They are composed of stars of nearly equal age and chemical composition, allowing us to use them as chronometers and as testbeds for gauging stellar evolution. It has become clear recently that massive stars are formed preferentially in close binaries, in which mass transfer will drastically change the evolution of the stars. This is expected to leave a significant imprint in the distribution of cluster stars in the Hertzsprung-Russell diagram. Our results, based on a dense model grid of more than 50,000 detailed binary-evolution calculations, indeed show several distinct, coeval main-sequence (MS) components, most notably an extended MS turnoff region, and a group of near-critical rotating stars that is spread over a large luminosity range on the red side of the classical MS. We comprehensively demonstrate the time evolution of the features in an animation, and we derive analytic expressions to describe these features. We find quantitative agreement with results based on recent photometric and spectroscopic observations. We conclude that while other factors may also be at play, binary evolution has a major impact on the MS morphology of young star clusters.

astro-ph.SR↗

arXiv2019

Generation and Measurement of High-order Optical Vortex via Cross-Phase

The generation and measurement of optical vortex (OV) are the basis for a variety of related applications. However, the special case of high-order OVs has not been sufficient addressed yet. Herein, a generation and measurement method of high-order OV via utilizing the CP is investigated. In the experiment, we generate OVs with l=60, p=20 and successfully measure OVs with l=200,p=0, where experimental results agree well with simulation outcome. On this basis, the intensity distributions of LG and HG beams (corresponding to the generation and measurement) versus waist radius of initial light beams is discussed. This work provides an alternative method to generate or measure high-order OV, which will facilitate applications in optical micro-manipulation, quantum entanglement and rotation speed detection.

physics.optics↗

arXiv2019

The Single Star Path to Be Stars

Be stars are rapidly rotating B main sequence stars, which show line emission due to an outflowing disc. By studying the evolution of rotating single star models, we can assess their contribution to the observed Be star populations. We identify the main effects which are responsible for single stars to approach critical rotation as functions of initial mass and metallicity, and predict the properties of populations of rotating single stars. We perform population synthesis with single star models of initial masses ranging between 3 and 30 solar masses, initial equatorial rotation velocities between 0 and 600 kms$^{-1}$ at compositions representing the Milky Way, Large and Small Magellanic Clouds. These models include efficient core-envelope coupling mediated by internal magnetic fields and correspond to the maximum efficiency of Be star production. We predict Be star fractions and the positions of fast rotating stars in the colour-magnitude diagram. We identify stellar wind mass-loss and the convective core mass fraction as the key parameters which determine the time dependance of the stellar rotation rates. Using empirical distributions of initial rotational velocities,our single star models can reproduce the trends observed in Be star fractions with mass and metallicity. However,they fail to produce a significant number of stars rotating very close to critical. We also find that rapidly rotating Be stars in the Magellanic Clouds should have significant surface nitrogen enrichments, which may be in conflict with abundance determinations of Be stars. Single star evolution may explain the high number of Be stars if 70 to 80% of critical rotationwould be sufficient to produce the Be phenomenon. However even in this case, the unexplained presence of many Be stars far below the cluster turn-off indicates the importance of the binary channel for Be star production.

astro-ph.SR↗

arXiv2019

Fully Dense Neural Network for the Automatic Modulation Recognition

Nowadays, we mainly use various convolution neural network (CNN) structures to extract features from radio data or spectrogram in AMR. Based on expert experience and spectrograms, they not only increase the difficulty of preprocessing, but also consume a lot of memory. In order to directly use in-phase and quadrature (IQ) data obtained by the receiver and enhance the efficiency of network extraction features to improve the recognition rate of modulation mode, this paper proposes a new network structure called Fully Dense Neural Network (FDNN). This network uses residual blocks to extract features, dense connect to reduce model size, and adds attentions mechanism to recalibrate. Experiments on RML2016.10a show that this network has a higher recognition rate and lower model complexity. And it shows that the FDNN model with dense connections can not only extract features effectively but also greatly reduce model parameters, which also provides a significant contribution for the application of deep learning to the intelligent radio system.

eess.SP↗

arXiv2019

Transferable Force-Torque Dynamics Model for Peg-in-hole Task

We present a learning-based force-torque dynamics to achieve model-based control for contact-rich peg-in-hole task using force-only inputs. Learning the force-torque dynamics is challenging because of the ambiguity of the low-dimensional 6-d force signal and the requirement of excessive training data. To tackle these problems, we propose a multi-pose force-torque state representation, based on which a dynamics model is learned with the data generated in a sample-efficient offline fashion. In addition, by training the dynamics model with peg-and-holes of various shapes, scales, and elasticities, the model could quickly transfer to new peg-and-holes after a small number of trials. Extensive experiments show that our dynamics model could adapt to unseen peg-and-holes with 70% fewer samples required compared to learning from scratch. Along with the learned dynamics, model predictive control and model-based reinforcement learning policies achieve over 80% insertion success rate. Our video is available at https://youtu.be/ZAqldpVZgm4.

cs.RO↗

arXiv2019

Energy cooperation in quantum thermoelectric systems with multiple electric currents

The energy efficiency and power of a quantum thermoelectric system with multiple electric currents and only one heat currents are studied. The system is connected to the hot heat bath with one terminal but the cold bath with multiple terminals or vice versal. We find that the cooperative effects can be a potentially useful tool in improving the energy efficiency and output power in multi-terminal mesoscopic thermoelectric systems. As an example, we show that the cooperation between the two thermoelectric effects in three-terminal thermoelectric systems leads to markedly improved performance of heat engine within the linear response regime using the Landauer-Bütiker formalism. Such improvement also emerge in four-terminal thermoelectric heat engines with three output electric currents. Cooperative effects in these multi-terminal thermoelectric systems can significantly enlarge the physical parameter region with high efficiency and power. For refrigeration, we find that the energy efficiency can also be substantially improved if multi-terminal configurations are considered, suggesting a useful scheme toward electronic cooling. Our study illustrates cooperative effects as a convenient approach toward high-performance thermoelectric energy conversion in multi-terminal mesoscopic systems.

cond-mat.mes-hall↗

arXiv2019

Scalar Quantization as Sparse Least Square Optimization

Quantization can be used to form new vectors/matrices with shared values close to the original. In recent years, the popularity of scalar quantization for value-sharing applications has been soaring as it has been found huge utilities in reducing the complexity of neural networks. Existing clustering-based quantization techniques, while being well-developed, have multiple drawbacks including the dependency of the random seed, empty or out-of-the-range clusters, and high time complexity for a large number of clusters. To overcome these problems, in this paper, the problem of scalar quantization is examined from a new perspective, namely sparse least square optimization. Specifically, inspired by the property of sparse least square regression, several quantization algorithms based on $l_1$ least square are proposed. In addition, similar schemes with $l_1 + l_2$ and $l_0$ regularization are proposed. Furthermore, to compute quantization results with a given amount of values/clusters, this paper designed an iterative method and a clustering-based method, and both of them are built on sparse least square. The paper shows that the latter method is mathematically equivalent to an improved version of k-means clustering-based quantization algorithm, although the two algorithms originated from different intuitions. The algorithms proposed were tested with three types of data and their computational performances, including information loss, time consumption, and the distribution of the values of the sparse vectors, were compared and analyzed. The paper offers a new perspective to probe the area of quantization, and the algorithms proposed can outperform existing methods especially under some bit-width reduction scenarios, when the required post-quantization resolution (number of values) is not significantly lower than the original number.

cs.LG↗