Higher-order Hamilton dynamics and Hamilton–Jacobi divergence PDE

This paper, using a non-standard Legendrian duality, investigates the Hamiltonian dynamics and formulates a Hamilton–Jacobi type divergence PDE governed by higher-order Lagrangians.     

Improving branch divergence performance on GPGPU with a new PDOM stack and multi-level warp scheduling

General-purpose graphics processing unit (GPGPU) plays an important role in massive parallel computing nowadays. A GPGPU core typically holds thousands of threads, where hardware threads are organized into warps. With the single instruction multiple thread (SIMT) pipeline, GPGPU can achieve high performance. But threads taking different branches in the same warp violate SIMD style and cause branch divergence. To support this, a hardware stack is used to sequentially execute all branches. Hence branch divergence leads to performance degradation. This article represents the PDOM (post dominator) stack as a binary tree, and each leaf corresponds to a branch target. We propose a new PDOM stack called PDOM-ASI, which can schedule all the tree leaves. The new stack can hide more long operation latencies with more schedulable warps without the problem of warp over-subdivision. Besides, a multi-level warp scheduling policy is proposed, which lets part of the warps run ahead and creates more opportunities to hide the latencies. The simulation results show that our policies achieve 10.5% performance improvements over baseline policies with only 1.33% hardware area overhead.     

Parameter identifiability with Kullback–Leibler information divergence criterion

We study the problem of parameter identifiability with Kullback–Leibler information divergence (KLID) criterion. The KLID‐identifiability is defined, which can be related to many other concepts of identifiability, such as the identifiability with Fisher's information matrix criterion, identifiability with least‐squares criterion, and identifiability with spectral density criterion. We also establish a simple check criterion for the Gaussian process and derive an upper bound for the minimal identifiable horizon of Markov process. Furthermore, we define the asymptotic KLID‐identifiability and prove that, under certain constraints, the KLID‐identifiability will be a sufficient or necessary condition for the asymptotic KLID‐identifiability. The consistency problems of several parameter estimation methods are also discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

基于DEMD的高压隔膜泵单向阀早期故障诊断

针对高压隔膜泵单向阀的早期故障特征提取困难的问题,提出基于微分经验模态分解(differential empirical mode decomposition,简称DEMD)的高压隔膜泵单向阀早期故障诊断方法。首先,对振动信号进行微分运算,提高高频成分的振幅比,使微弱高频成分在后续分解中更易提取;其次,对得到的新信号进行经验模态分解(empirical mode decomposition,简称EMD),并将分解后的本征模函数(intrinsic mode function,简称IMF)分量信号进行积分还原;最后,计算分量信号与原振动信号的Kullback-Leibler散度(Kullback-Leibler divergence,简称K-L散度)值,选取K-L散度值较小的分量信号进行重构,并利用Hilbert边际谱对重构信号进行瞬时频谱分析,以提取故障振动信号的特征。仿真与工程实验分析表明,该方法能够较好地提取出单向阀早期故障特征信息。     

扩压器型面局部张角的计算及附面层修正

本文主要研究成果是对采用等压力梯度及等速度梯造型规律的扩压器各截面型面局部张角提供了一种精确的理论计算方法。并为采用参考文献[3]进行扩压器附面层位移厚度的计算提供了条件。     

Poitín: Distilling Theorems From Conjectures

In this paper, we describe a new fully automatic theorem prover called Poitín which makes use of a novel transformation algorithm called distillation to prove input conjectures. The input conjectures are defined in a functional language and are transformed using the distillation algorithm. The result of this transformation can be easily inspected to see whether the original conjecture is true. Possible divergence of the transformation algorithm is detected, and this information is used to perform generalizations to ensure termination. We give several examples of the application of the theorem prover, and compare it to related work.     

无穷级数的解题方法

本揭示了数基级数和幂级数之间的内在联系，并总结出解答无穷级数习题的较为简洁的方法。     

内腔式KTP OPO发散角的实验研究

实验研究了非临界相位匹配 (NCPM)的内腔式KTP光学参量振荡器 (OPO)的光束发散角与OPO谐振腔参数的关系。证明了望远镜型共焦非稳谐振腔是压缩OPO光束发散角的有效方法。     

基于信息论的连续属性离散化

使用信息论的方法进行连续属性的离散化，引入Hellinger偏差HD（Hellinger Divergence)作为每个区间对决策的信息量度量，从而定义切分点的信息熵，最终的离散化结果是使各区间的信息量尽可能平均，分析了HD度量在两种离散化方法中的作用，说明它在划分算法中运用比较理想，而在归并算法中则有局限。     

用角放大率判定光学系统与光束性质

用两种光束入射，通过举例来说明，如何通过角放大率的大小和正负来判定光学系统和出射光束的性质。