How good is a Broyden–Fletcher–Goldfarb–Shanno-like update Hessian formula to locate transition structures? Specific reformulation of Broyden–Fletcher–Goldfarb–Shanno for optimizing saddle points

Based on a study of the Broyden–Fletcher–Goldfarb–Shanno (BFGS) update Hessian formula to locate minima on a hypersurface potential energy, we present an updated Hessian formula to locate and optimize saddle points of any order that in some sense preserves the initial structure of the BFGS update formula. The performance and efficiency of this new formula is compared with the previous updated Hessian formulae such as the Powell and MSP ones. We conclude that the proposed update is quite competitive but no more efficient than the normal updates normally used in any optimization of saddle points. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 349–362, 1998     

基于Intra帧刷新的差错控制新方法

面向IP网,本文分析了传统的基于帧内编码(Intra)帧周期刷新机制的性能,针对其编码效率低的缺点,提出了基于敏感度和反馈信息刷新的两种新方法.这两种方法不仅保持了周期刷新对差错的自恢复能力,而且在很大程度上改善了编码效率.     

Tracking an Auto-Regressive Process with Limited Communication per Unit Time

Samples from a high-dimensional first-order auto-regressive process generated by an independently and identically distributed random innovation sequence are observed by a sender which can communicate only finitely many bits per unit time to a receiver. The receiver seeks to form an estimate of the process value at every time instant in real-time. We consider a time-slotted communication model in a slow-sampling regime where multiple communication slots occur between two sampling instants. We propose a successive update scheme which uses communication between sampling instants to refine estimates of the latest sample and study the following question: Is it better to collect communication of multiple slots to send better refined estimates, making the receiver wait more for every refinement, or to be fast but loose and send new information in every communication opportunity? We show that the fast but loose successive update scheme with ideal spherical codes is universally optimal asymptotically for a large dimension. However, most practical quantization codes for fixed dimensions do not meet the ideal performance required for this optimality, and they typically will have a bias in the form of a fixed additive error. Interestingly, our analysis shows that the fast but loose scheme is not an optimal choice in the presence of such errors, and a judiciously chosen frequency of updates outperforms it.     

空闲状态下信令缩减机制的研究

在移动通信系统中,当多模终端跨系统进行小区重选时,需要进行位置区域更新。如果频繁跨越不同系统,终端会反复进行位置更新,从而使空口和网络产生大量的位置区域更新信令。为了解决这一问题,在LTE/SAE部署初期,引入了空闲状态下信令缩减机制——ISR（Idle State Signaling Reduction）。本文介绍了ISR机制提出的背景,分析了添加ISR机制后的网络架构及ISR机制的关键参数,说明了ISR机制的相关过程。     

LEO卫星网基于时间和距离的位置更新策略

针对LEO卫星网中的动态位置区划分提出的一种基于时间和距离的位置更新策略,不同以往的处理方式,提出的更新策略中动态位置区更新半径随着用户的运动速度和业务繁忙程度而改变,对高速用户和低速用户分别采用不同的更新半径,当系统的业务繁忙程度改变时更新半径也相应的改变,仿真结果表明文中提出的位置更新策略对于移动用户比较多并且业务突发情况,能有效的减少位置管理开销,节省了系统资源。     

Mean-square performance analysis of the family of selective partial update and selective regressor affine projection algorithms

In this paper we present a general formalism for the establishment and mean-square performance analysis of the family of selective partial update affine projection (SPU-AP), selective regressor affine projection (SR-AP), and selective partial update subband adaptive filter (SPU-SAF) algorithms. This analysis is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. We demonstrate through simulations that the results are useful in predicting the performance of these adaptive filter algorithms.     

Improvements to message computation in lazy propagation

Even though existing algorithms for belief update in Bayesian networks (BNs) have exponential time and space complexity, belief update in many real-world BNs is feasible. However, in some cases the efficiency of belief update may be insufficient. In such cases minor improvements in efficiency may be important or even necessary to make a task tractable. This paper introduces two improvements to the message computation in Lazy propagation (LP): (1) we introduce myopic methods for sorting the operations involved in a variable elimination using arc-reversal and (2) extend LP with the any-space property. The performance impacts of the methods are assessed empirically.     

软件定义网络中快速和一致的流更新策略

在软件定义网络中,为了实现各种网络性能优化目标,控制面需要频繁的对数据面进行更新.然而,由于数据面的异步性,不合理的更新将严重降低网络性能.针对此问题,该文提出一种快速和一致的流更新策略(FCFU).该策略通过流分段减弱其原有的强依赖关系,使能并行更新,通过分析子流段与多个资源间的依赖关系得到总更新轮数较少的更新安排,...     

基于拥挤度因子的动态信息素更新策略蚁群算法

针对蚁群算法易陷入局部最优、收敛速度慢的问题,文中提出了一种基于拥挤度因子的动态信息素更新策略的蚁群算法(CFACS)。引入鱼群算法中拥挤度的思想,扩大种群中蚂蚁分布范围,使其探索更大的解空间,提高算法全局搜索能力;采用动态信息素更新策略,在每一次迭代中,自适应调整当前最优路径所释放的信息素浓度,保证蚁群前期的多样性,同时保证算法在后期的收敛性。求解TSP问题的仿真实验表明,改进算法求得解的质量和求解的收敛速度都明显优于传统蚁群算法,较好地平衡了种群多样性与收敛速度之间的矛盾。     

基于离线调度的电泳式类纸显示屏多通道刷新研究

类纸显示屏由于其所具有的自然性,已经被认为是在未来的普适计算环境中一种不可或缺的显示材料。文章针对类纸屏控制器的多通道刷新原理进行分析,提出了一种基于离线调度的多通道刷新调度方法。通过数学证明,该方法在保证显示顺序依赖的前提下,可以对队列中的多刷新任务实现在获得最优显示时间下的并行刷新任务划分。