arXiv subjects

Na Li

Publications and source records attributed to Na Li.

At least 271 records · Page 15Linked to original sources

arXiv2019

Inducing Uniform Asymptotic Stability in Non-Autonomous Accelerated Optimization Dynamics via Hybrid Regularization

There have been many recent efforts to study accelerated optimization algorithms from the perspective of dynamical systems. In this paper, we focus on the robustness properties of the time-varying continuous-time version of these dynamics. These properties are critical for the implementation of accelerated algorithms in feedback-based control and optimization architectures. We show that a family of dynamics related to the continuous-time limit of Nesterov's accelerated gradient method can be rendered unstable under arbitrarily small bounded disturbances. Indeed, while solutions of these dynamics may converge to the set of optimizers, in general, this set may not be uniformly asymptotically stable. To induce uniformity, and robustness as a byproduct, we propose a framework where we regularize the dynamics by using resetting mechanisms that are modeled by well-posed hybrid dynamical systems. For these hybrid dynamics, we establish uniform asymptotic stability and robustness properties, as well as convergence rates that are similar to those of the non-hybrid dynamics. We finish by characterizing a family of discretization mechanisms that retain the main stability and robustness properties of the hybrid algorithms.

math.OC↗

arXiv2019

Exploiting Fast Decaying and Locality in Multi-Agent MDP with Tree Dependence Structure

This paper considers a multi-agent Markov Decision Process (MDP), where there are $n$ agents and each agent $i$ is associated with a state $s_i$ and action $a_i$ taking values from a finite set. Though the global state space size and action space size are exponential in $n$, we impose local dependence structures and focus on local policies that only depend on local states, and we propose a method that finds nearly optimal local policies in polynomial time (in $n$) when the dependence structure is a one directional tree. The algorithm builds on approximated reward functions which are evaluated using locally truncated Markov process. Further, under some special conditions, we prove that the gap between the approximated reward function and the true reward function is decaying exponentially fast as the length of the truncated Markov process gets longer. The intuition behind this is that under some assumptions, the effect of agent interactions decays exponentially in the distance between agents, which we term "fast decaying property".

math.OC↗

arXiv2019

Optimal Distributed Feedback Voltage Control under Limited Reactive Power

In this paper, we propose a distributed voltage control in power distribution networks through reactive power compensation. The proposed control can (i) operate in a distributed fashion where each bus makes its decision based on local voltage measurements and communication with neighboring buses, (ii) always satisfy the reactive power capacity constraint, (iii) drive the voltage magnitude into an acceptable range, and (iv) minimize an operational cost. We also perform various numerical case studies to demonstrate the effectiveness and robustness of the controller using the nonlinear power flow model.

math.OC↗

arXiv2019

The electron transfer dynamics in the contact electrification and its effects on the intensity of triboluminescence

With the growing threat of energy crisis and the increasing need to power microelectronic devices, people are seeking potential alternative energies that can replace the conventional sources such as fossil fuels. Due to its simple structure, low cost, and high performance, the triboelectric nanogenerator (TENG) which is based on the contact electrification has become one of the most promising candidates. Although plays a crucial role in determining the amount of charge transfer of TENG, the fundamental mechanism that underlies the charge transfer in the contact electrification of insulator-insulator contacts has still not been completely understood. In this paper, the dynamics of charge transfer in the contact electrification is investigated by observing the triboluminescence of the sliding contacts and a theoretical model is proposed for the electrification of insulator-insulator contacts. In the present "Capacitor model", the electron tunneling is assumed to be the dominating mechanism in the electrification and the driving force for the electron transfer is the contact potential difference, and thus, the electrification is considered as a charging process of the capacitor formed by the contact surfaces. The consistency between the predictions by the present model and the experiments may confirm again that the electron transfer is the dominant process in the contact electrification of insulator-insulator contacts.

physics.app-ph↗

arXiv2019

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images

Current VHR(Very High Resolution) satellite images enable the detailed monitoring of the earth and can capture the ongoing works of railway construction. In this paper, we present an integrated framework applied to monitoring the railway construction in China, using QuickBird, GF-2 and Google Earth VHR satellite images. We also construct a novel DCNNs-based (Deep Convolutional Neural Networks) semantic segmentation network to label the temporary works such as borrow & spoil area, camp, beam yard and ESAs(Environmental Sensitive Areas) such as resident houses throughout the whole railway construction project using VHR satellite images. In addition, we employ HED edge detection sub-network to refine the boundary details and attention cross entropy loss function to fit the sample class disequilibrium problem. Our semantic segmentation network is trained on 572 VHR true color images, and tested on the 15 QuickBird true color images along Ruichang-Jiujiang railway during 2015-2017. The experiment results show that compared with the existing state-of-the-art approach, our approach has obvious improvements with an overall accuracy of more than 80%.

cs.CV↗

arXiv2019

On Energy Compaction of 2D Saab Image Transforms

The block Discrete Cosine Transform (DCT) is commonly used in image and video compression due to its good energy compaction property. The Saab transform was recently proposed as an effective signal transform for image understanding. In this work, we study the energy compaction property of the Saab transform in the context of intra-coding of the High Efficiency Video Coding (HEVC) standard. We compare the energy compaction property of the Saab transform, the DCT, and the Karhunen-Loeve transform (KLT) by applying them to different sizes of intra-predicted residual blocks in HEVC. The basis functions of the Saab transform are visualized. Extensive experimental results are given to demonstrate the energy compaction capability of the Saab transform.

eess.IV↗

arXiv2019

On the Equivalence of Youla, System-level and Input-output Parameterizations

A convex parameterization of internally stabilizing controllers is fundamental for many controller synthesis procedures. The celebrated Youla parameterization relies on a doubly-coprime factorization of the system, while the recent system-level and input-output characterizations require no doubly-coprime factorization but a set of equality constraints for achievable closed-loop responses. In this paper, we present explicit affine mappings among Youla, system-level and input-output parameterizations. Two direct implications of the affine mappings are 1) any convex problem in Youla, system level, or input-output parameters can be equivalently and convexly formulated in any other one of these frameworks, including the convex system-level synthesis (SLS); 2) the condition of quadratic invariance (QI) is sufficient and necessary for the classical distributed control problem to admit an equivalent convex reformulation in terms of Youla, system-level, or input-output parameters.

math.OC↗

arXiv2019

Accelerated Distributed Nesterov Gradient Descent

This paper considers the distributed optimization problem over a network, where the objective is to optimize a global function formed by a sum of local functions, using only local computation and communication. We develop an Accelerated Distributed Nesterov Gradient Descent (Acc-DNGD) method. When the objective function is convex and $L$-smooth, we show that it achieves a $O(\frac{1}{t^{1.4-ε}})$ convergence rate for all $ε\in(0,1.4)$. We also show the convergence rate can be improved to $O(\frac{1}{t^2})$ if the objective function is a composition of a linear map and a strongly-convex and smooth function. When the objective function is $μ$-strongly convex and $L$-smooth, we show that it achieves a linear convergence rate of $O([ 1 - C (\fracμ{L})^{5/7} ]^t)$, where $\frac{L}μ$ is the condition number of the objective, and $C>0$ is some constant that does not depend on $\frac{L}μ$.

math.OC↗

arXiv2019

Aggregate Power Flexibility in Unbalanced Distribution Systems

With a large-scale integration of distributed energy resources (DERs), distribution systems are expected to be capable of providing capacity support for the transmission grid. To effectively harness the collective flexibility from massive DER devices, this paper studies distribution-level power aggregation strategies for transmission-distribution interaction. In particular, this paper proposes a method to model and quantify the aggregate power flexibility, i.e., the net power injection achievable at the substation, in unbalanced distribution systems over time. Incorporating the network constraints and multi-phase unbalanced modeling, the proposed method obtains an effective approximate feasible region of the net power injection. For any aggregate power trajectory within this region, it is proved that there exists a feasible disaggregation solution. In addition, a distributed model predictive control (MPC) framework is developed for the practical implementation of the transmission-distribution interaction. At last, we demonstrate the performances of the proposed method via numerical tests on a real-world distribution feeder with 126 multi-phase nodes.

eess.SY↗

arXiv2019

Learning discriminative features in sequence training without requiring framewise labelled data

In this work, we try to answer two questions: Can deeply learned features with discriminative power benefit an ASR system's robustness to acoustic variability? And how to learn them without requiring framewise labelled sequence training data? As existing methods usually require knowing where the labels occur in the input sequence, they have so far been limited to many real-world sequence learning tasks. We propose a novel method which simultaneously models both the sequence discriminative training and the feature discriminative learning within a single network architecture, so that it can learn discriminative deep features in sequence training that obviates the need for presegmented training data. Our experiment in a realistic industrial ASR task shows that, without requiring any specific fine-tuning or additional complexity, our proposed models have consistently outperformed state-of-the-art models and significantly reduced Word Error Rate (WER) under all test conditions, and especially with highest improvements under unseen noise conditions, by relative 12.94%, 8.66% and 5.80%, showing our proposed models can generalize better to acoustic variability.

cs.LG↗

arXiv2019

Exponential Stability of Primal-Dual Gradient Dynamics with Non-Strong Convexity

This paper studies the exponential stability of primal-dual gradient dynamics (PDGD) for solving convex optimization problems where constraints are in the form of Ax+By= d and the objective is min f(x)+g(y) with strongly convex smooth f but only convex smooth g. We show that when g is a quadratic function or when g and matrix B together satisfy an inequality condition, the PDGD can achieve global exponential stability given that matrix A is of full row rank. These results indicate that the PDGD is locally exponentially stable with respect to any convex smooth g under a regularity condition. To prove the exponential stability, two quadratic Lyapunov functions are designed. Lastly, numerical experiments further complement the theoretical analysis.

eess.SY↗

arXiv2019

Voltage Control Using Limited Communication

In electricity distribution networks, the increasing penetration of renewable energy generation necessitates faster and more sophisticated voltage controls. Unfortunately, recent research shows that local voltage control fails in achieving the desired regulation, unless there is communication between the controllers. However, the communication infrastructure for distribution systems is less reliable and less ubiquitous as compared to that for the bulk transmission system. In this paper, we design distributed voltage control that uses limited communication. That is, only neighboring buses need to communicate a few bits between each other for each control step. We investigate how these controllers can achieve the desired asymptotic behavior of the voltage regulation and we provide upper bounds on the number of bits that are needed to ensure a predefined accuracy of the regulation. Finally, we illustrate the results by numerical simulations.

math.OC↗

arXiv2018

Relationship between Characteristic Lengths and Effective Saffman Length in Colloidal Monolayers near a Water-Oil Interface

The hydrodynamic interactions (HIs) in colloidal monolayers are strongly influenced by the boundary conditions and can be directly described in terms of the cross-correlated diffusion of the colloid particles. In this work, we experimentally measured the cross-correlated diffusion in colloidal monolayers near a water-oil inter-face. The characteristic lengths of the system were obtained by introducing an effec-tive Saffman length. The characteristic lengths of a particle monolayer near a water-oil interface were found to be anisotropic in the longitudinal and transverse directions. From these characteristic lengths, the master curves of cross-correlated diffusion are obtained, which universally describe the HIs near a liquid-liquid interface.

cond-mat.soft↗

arXiv2018

Anisotropic Characteristic Lengths of Colloidal Monolayers Near a Water-Air Interface

Near-interface colloidal monolayers have often been used as model systems for research on hydrodynamics in biophysics and microfluidic systems. Using optical microscopy and multiparticle tracking techniques, the correlated diffusion of particles is experimentally measured in colloidal monolayers near a water-air interface. It is found that the characteristic lengths X1 and X2 of such a colloidal monolayer are anisotropic in these two perpendicular directions. The former (X1)is equal to the Saffman length of the monolayer and reflects the continuous nature of the system in the longitudinal direction. The latter (X2)is a function of both the Saffman length and the radius of the colloids and reflects the discrete nature of the system in the transverse direction. This discovery demonstrates that the hydrodynamics intrinsically follow different rules in these two directions in this system.

cond-mat.soft↗

arXiv2018

On the Exponential Stability of Primal-Dual Gradient Dynamics

Continuous time primal-dual gradient dynamics that find a saddle point of a Lagrangian of an optimization problem have been widely used in systems and control. While the global asymptotic stability of such dynamics has been well-studied, it is less studied whether they are globally exponentially stable. In this paper, we study the primal-dual gradient dynamics for convex optimization with strongly-convex and smooth objectives and affine equality or inequality constraints, and prove global exponential stability for such dynamics. Bounds on decaying rates are provided.

math.OC↗

arXiv2017

Convergence of Limited Communications Gradient Methods

Distributed optimization increasingly plays a central role in economical and sustainable operation of cyber-physical systems. Nevertheless, the complete potential of the technology has not yet been fully exploited in practice due to communication limitations posed by the real-world infrastructures. This work investigates fundamental properties of distributed optimization based on gradient methods, where gradient information is communicated using limited number of bits. In particular, a general class of quantized gradient methods are studied where the gradient direction is approximated by a finite quantization set. Sufficient and necessary conditions are provided on such a quantization set to guarantee that the methods minimize any convex objective function with Lipschitz continuous gradient and a nonempty and bounded set of optimizers. A lower bound on the cardinality of the quantization set is provided, along with specific examples of minimal quantizations. Convergence rate results are established that connect the fineness of the quantization and the number of iterations needed to reach a predefined solution accuracy. Generalizations of the results to a relevant class of constrained problems using projections are considered. Finally, the results are illustrated by simulations of practical systems.

math.OC↗

arXiv2017

Pure Even Harmonic Generation from Oriented CO in Linearly Polarized Laser Fields

The first high harmonic spectrum, containing only the odd orders, was observed in experiments 30 years ago (1987). However, a spectrum containing pure even harmonics has never been observed. We investigate the generation of pure even harmonics from oriented CO molecules in linearly polarized laser fields employing the time-dependent density-functional theory. We find that the even harmonics, with no odd orders, are generated with the polarization perpendicular to the laser polarization, when the molecular axis of CO is perpendicular to the laser polarization. Generation of pure even harmonics reveals a type of dipole acceleration originating from the permanent dipole moment. This phenomenon exists in all system with permanent dipole moments, including bulk crystal and polyatomic molecules.

physics.optics↗

arXiv2017

Effects of the Position Reversal of Friction Pairs on the Strength of Tribocharging and Tribodischarging

The friction-induced charging (i.e., tribocharging) and the following discharging (referred here as tribodischarging) are always believed to have negative effects on the daily life and on the industrial production. Thus, how to inhibit the tribocharging and the tribodischarging has caused wide public concern. Because the discharge caused by the electrical breakdown of the ambient gas is generally accompanied with the generation of light, we investigated here the tribocharging and the tribodischarging by observing the light emitted during friction. We found that the position reversal of the friction pair has a dramatic impact on the intensity of the tribo-induced light. Experimental results show that an intense light is produced when a stationary Al2O3 disk is sliding on a rotating SiO2 disk, but only a weak light is observed for the case of a stationary SiO2 disk and a rotating Al2O3 disk. This means that the process of the tribocharging and the tribodischarging can be significantly influenced owing to the change in the relative position of the friction couple. The experimentally measured polarities of the tribo-induced charge on the friction surfaces further indicated that the strong discharging occurs when the rotating surface is negatively charged. The reason for the difference in the intensity of the tribocharging and tribodischarging can be attributed to the combined effects of the contact potential difference and the temperature gradient between the contacting surfaces on the charge transfer when friction. Finally, a simple, low cost, yet effective approach, i.e., just keep the friction partner whose surface is tribo-induced negatively charged as the stationary one, can be utilized to suppress the intensity of the tribocharging and the tribodischarging. This work may provide potential applications in numerous areas of science and engineering and also in the everyday life.

cond-mat.mtrl-sci↗