Boundedness of Hausdorff operators on the power weighted Hardy spaces

In this paper, we consider the two-dimensional Hausdorff operators on the power weighted Hardy space H;（R;） （ -1 ≤α≤0）, defined by H;f（x）=∫R;Φ（u）f(A（u）x)du,where Φ∈L;oc;（R;）,A（u） = (α;（u）);is a 2×2 matrix, and each α;is a measurablefunction.We obtain that HΦ,A is bounded from H;（R;） （ -1≤α≤0） to itself, if∫R2|Φ（u）‖det A;（u）|‖A（u）‖;ln(1+‖A;（u）‖;/|det A;（u）|)du<∞.This result improves some known theorems, and in some sense it is sharp.

Endpoint Estimates for Hardy Operator's Conjugate Operator with Power Weight on n-Dimensional Space

In this paper, we establish two integral inequalities for Hardy operator＇s conjugate operator at the endpoint on n-dimensional space. The operator Hn is bounded from Lxα1 （Gn） to Lxβq （Gn） with the bound explicitly worked out and the similar result holds for Hn＊.

LDPC-Coded OFDM Transmission Based on Adaptive Power Weights in Cognitive Radio Systems

In this paper, we propose a new scheme to improve the performance of an LDPC-coded OFDM based cognitive radio (CR) link by applying adaptive power weights. To minimize estimation errors of detected signals in all the CR subcarriers, power weights are allocated to the CR subcarriers at the secondary transmitter. Some constraints for the power weights are considered, such as keeping the interference power introduced by the CR to primary users below a given interference threshold and also keeping sum of transmission powers in all CR subcarriers within a total transmission power. The LDPC decoder applies these power weights in the Log Likelihood Ratios (LLRs) used in message passing scheme at the secondary receiver to achieve more reliable communications. So, the received signal in each CR subcarrier will be decoded with the knowledge of transmission power weights, which come from the cognitive feedback channel without additional cost. Simulation results demonstrate that our proposed scheme achieves a lower bit error rate and a higher transmission rate compared with those of the same scheme without applying power weights.

Explicit constants for Hardy’s inequality with power weight on n-dimensional product spaces

In this paper, Hardy operator H on n-dimensional product spaces G = (0, ∞)n and its adjoint operator H* are investigated. We use novel methods to obtain two main results. One is that we characterize the sufficient and necessary conditions for the operators H and H* being bounded from Lp(G, xα) to Lq(G, xβ), and the bounds of the operators H and H* are explicitly worked out. The other is that when 1 < p = q < +∞, norms of the operators H and H* are obtained.

L^2 NORM INEQUALITY WITH POWER WEIGHTS FOR THE MAXIMAL RIESZ SPHERICAL MEANS

We have pointed out in [1] that so far the L^2 norm inequalities with power weights for the Riesz means σ_R~δ(g)(x) of multiple Fourier integrals have been obtained only by Hirschman and J. L. Rubio de Francia respectively:

Generalizations of mixed weighted power mean inequality

Tarnavas established mixed weighted power mean inequality in 1999. A separation of weighted power mean inequslity was derived in this paper. As its applications, some separations of other inequalities were given.

INVERSE POWER METHOD AND WEIGHTED SOBOLEV SPACES

1. Introduction This paper is a continuation of the paper [5]. Now we want to treat the problem

Properties, Inference and Applications of Inverse Power Two-Parameter Weighted Lindley Distribution

We proposed “a new extension of three-parametric distribution” called the inverse power two-parameter weighted Lindley (IPWL) distribution capable of modeling a upside-down bathtub hazard rate function. This distribution is studied to get basic structural properties such as reliability measures, moments, inverse moments and its related measures. Simulation studies are done to present the performance and behavior of maximum likelihood estimates of the IPWL distribution parameters. Finally, we perform goodness of fit measures and test statistics using a real data set to show the performance of the new distribution.

Differentiation degree combination weighting method for investment decision-making risk assessment in power grid construction projects

Power grid construction projects are distinguished by their wide variety,high investment,long payback period,and close relation to national development and human welfare.To improve the investment accuracy in such projects and effectively prevent investment risks,this paper proposes an investment optimization decision-making method for multiple power grid construction projects under a certain investment scale.Firstly,an in-depth analysis of the characteristics and development requirements of China’s power grid projects was performed.Thereafter,the time sequence and holographic method was adopted to conduct multi-dimensional,multi-perspective risk assessment of different parts of power grid projects,and a holographic risk assessment index system was developed.Moreover,an investment decision model considering the comprehensive risk based on combination weighting was developed according to the output and input of power grid construction projects.A new combination weighting optimization method that takes into account the investment willingness of enterprises was designed to improve the current weighting evaluation methods.Finally,the validity and applicability of the proposed evaluation method were verified by case examples.

Apply the Double-Weight Neural Network to Dynamic Power Management

This paper expounds a data-fitting algorithm for the double-weight neural network,and presents a new algorithm for the system's power management on the base of that.The double-weight neural network learns knowledge from the past idle periods of the system,and predicts the lengths of the coming idle periods.As a result of that,the system can switch its running states and re- duce the power dissipation according to the predictive values.The results of the experiments prove that this algorithm shows a better performance in increasing the right rate of shutting down and reducing the power consumption than other traditional ones.

Wide-Area Delay-Dependent Adaptive Supervisory Control of Multi-machine Power System Based on Improve Free Weighting Matrix Approach

The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).

Dynamic Equivalent Method of Motor Loads for Power Systems Based on the Weighted

Dynamic equivalence can not only largely reduce the system size and the computation time but also stress the dominant features of the system [1]-[3]. This paper firstly recommends the basic concept of dynamic equivalent and the status of both domestic and abroad development in this area. The most existing equivalent methods usually only deal with static load models and neglect the dynamic characteristics of loads such as induction motors. In addition, the existing polymerization method which is based on the frequency domain algorithm of induction electric machines parameters takes a long time to equivalent for the large system, then the new method based on the weighted is proposed. Then, the basic steps for dynamic equivalence with the weighted method are introduced as follows. At first, the clustering criterion of motor loads based on time domain simulation is given. The motors with similar dynamic characteristics are classified into one group. Then, the simplication of the buses of motors in same group and network is carried out. Finally, parameters of the equivalent motor are calculated and the equivalent system is thus obtained based on the weighted. This aggregation method is applied to the simple distribution system of 4 generators. Simulation results show that the method can quickly obtain polymerization parameters of generator groups and the aggregation model retains the dynamic performance of the original model with good accuracy, the active and reactive power fitting error is smaller as well.

WEIGHTED ESTIMATE FOR THE MULTILINEAR OSCILLATORY SINGULAR INTEGRAL OPERATORS

In this paper, the weighted Lp(Rn) boundedness for the multilinear oscillatory singular integral operators with polynomial phases is studied.

Power图的性质及构造算法研究

点集的 Power图是点集 Voronoi图的推广 ,特别适合用来解决涉及球 (圆 )的几何问题 .文中首先对 Power图的基本性质进行了几何化的证明 ;之后 ,研究了权为负数时对 Power图的影响 ,指出在 Power图的理论中允许权为负数 ,从而 Power图可以应用到具有负权性质的领域 ;最后 ,给出了平面点集的 Power图的构造算法 ,该算法利用 Power图与正则三角化互为对偶的原理 ,在点集的正则三角化的基础上构造 Power图 ,同时给出了实例以说明算法的有效性 .

一种用于深空网天线组阵的基于归一化权的Matrix-Free Power Method

对深空网天线组阵中的几种信号相关算法作简要介绍,重点研究无需形成矩阵的幂的方法——Matrix-Free Power Method。通过理论分析,提出一种改进算法,即基于归一化权的Matrix-Free Power Method。理论计算和软件仿真结果均表明,基于归一化权的Matrix-Free Power Method信噪比合成性能略优于原Matrix-Free Power Method。

三维精确power图的GPU并行计算

power图(加权Voronoi图)的计算是计算机图形学和计算几何等领域的一项基础任务.针对求解三维power图的传统串行方法所需的时间成本较高,且现有并行算法所得结果为近似解,提出一种新颖的GPU并行计算方法.首先给出power图与高一维受限Voronoi图的等价构造方法,将Voronoi图的无网格方法直接推广到power图的计算.因此,给定的加权种子点被置于更高一维空间中的一组方格内,据此快速搜索每个种子点的邻居关系,进而使用各个种子点与其若干个邻居的中垂面对各自的power胞元进行并行裁剪,以快速地获取三维空间中的精确power图.对比不同求解域下和5万个种子点的计算耗时,比现有方法具有超过3倍的加速比.

Joint Subcarrier and Power Allocation for Multi-UAV Systems

This paper investigates subcarrier and power allocation in a multi-UAV OFDM system.The study considers a practical scenario,where certain subcarriers are unavailable for dynamic subcarrier allocation,on account of pre-allocation for burst transmissions.We first propose a novel iterative algorithm to jointly optimize subcarrier and power allocation,so as to maximize the sum rate of the uplink transmission in the multiUAV OFDM system.The key idea behind our solution is converting the nontrivial allocation problem into a weighted mean square error(MSE) problem.By this means,the allocation problem can be solved by the alternating optimization method.Besides,aiming at a lower-complexity solution,we propose a heuristic allocation scheme,where subcarrier allocation and transmit power allocation are separately optimized.In the heuristic scheme,closedform solution can be obtained for power allocation.Simulation results demonstrate that in the presence of stretched subcarrier resource,the proposed iterative joint optimization algorithm can significantly outperform the heuristic scheme,offering a higher sum rate.

基于幂加权最小二乘拟合的红外相机辐射定标方法

分析了现有线性度计算方法的不足,提出基于偏差/测量值的新线性度评价方式,通过该方式最小二乘拟合的低端温度偏差比高端大一个数量级,并采用加权拟合提高系统响应线性度。在分析不同光谱的温度和辐亮度拟合函数基础上,提出一种基于辐亮度倒数幂加权最小二乘线性拟合的地面和星上辐射定标方法,确认最佳权重幂次,建立了幂次n=1的加权最小二乘拟合外黑体线性定标方程、内黑体线性定标方程、内外黑体辐亮度转换模型。针对星上内黑体高精度两点定标建立了基于加权最小二乘拟合内外黑体辐亮度转换模型;针对星上黑体发射率退化提出了基于恒星定标的红外相机星上内黑体辐亮度定标修正方法,建立了外黑体辐亮度、内黑体辐亮度和恒星辐亮度转换模型。采用加权线性拟合后,积分时间10 ms的低温端外黑体反演偏差由1.63 K下降到0.52 K,内黑体偏差反演温度偏差由0.83 K下降到0.39 K,系统响应线性度明显提升。

Randomly Weighted Averages on Order Statistics

We study a well-known problem concerning a random variable uniformly distributed between two independent random variables. Two different extensions, randomly weighted average on independent random variables and randomly weighted average on order statistics, have been introduced for this problem. For the second method, two-sided power random variables have been defined. By using classic method and power technical method, we study some properties for these random variables.

采用改进MPC提高储能系统电压暂态特性研究

储能系统通过换流器实现并网运行,常规换流器因为其开关频率低,在采样、计算环节存在延时导致储能系统暂态特性差,甚至引起整个电网不稳定。本文采用模型预测控制MPC(model predictive control)来实现储能系统功率快速响应,避免延时影响。引入功率权重价值函数在有功、无功MPC控制中,计算储能换流器输出电压最优值。针对因为滤波电感参数偏移导致的MPC模型不准确问题,本文采用电感误差补偿控制来提高模型精度。通过Matlab/Simulink仿真和实验来验证本文所提方案可提高储能系统暂态特性,有效消除误差对MPC控制性能的影响。