Weighted dynamic time warping for time series classification

Dynamic time warping (DTW), which finds the minimum path by providing non-linear alignments between two time series, has been widely used as a distance measure for time series classification and clustering. However, DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point. This may lead to misclassification especially in applications where the shape similarity between two sequences is a major consideration for an accurate recognition. Therefore, we propose a novel distance measure, called a weighted DTW (WDTW), which is a penalty-based DTW. Our approach penalizes points with higher phase difference between a reference point and a testing point in order to prevent minimum distance distortion caused by outliers. The rationale underlying the proposed distance measure is demonstrated with some illustrative examples. A new weight function, called the modified logistic weight function (MLWF), is also proposed to systematically assign weights as a function of the phase difference between a reference point and a testing point. By applying different weights to adjacent points, the proposed algorithm can enhance the detection of similarity between two time series. We show that some popular distance measures such as DTW and Euclidean distance are special cases of our proposed WDTW measure. We extend the proposed idea to other variants of DTW such as derivative dynamic time warping (DDTW) and propose the weighted version of DDTW. We have compared the performances of our proposed procedures with other popular approaches using public data sets available through the UCR Time Series Data Mining Archive for both time series classification and clustering problems. The experimental results indicate that the proposed approaches can achieve improved accuracy for time series classification and clustering problems.     

Face recognition based on 2D images under illumination and pose variations

We propose a novel 2D image-based approach that can simultaneously handle illumination and pose variations to enhance face recognition rate. It is much simpler, requires much less computational effort than the methods based on 3D models, and provides a comparable or better recognition rate.     

Stability radius of implicit dynamic equations with constant coefficients on time scales

This paper deals with the stability radii of implicit dynamic equations on time scales when the structured perturbations act on both the coefficient of derivative and the right-hand side. Formulas of the stability radii are derived as a unification and generalization of some previous results. A special case where the real stability radius and the complex stability radius are equal is studied. Examples are derived to illustrate results.     

基于Δ-Σ技术和FPGA的数据采集系统

为了改善传统数据采集系统运算能力差、分辨率低、可靠性低等缺点,结合Δ-Σ技术和FPGA,设计了一种多通道、高分辨率、宽动态范围的新型数据采集系统。提出了一种由Δ-ΣA/D转换芯片、高性能FPGA和DSP组成的数据采集系统方案及其硬件电路实现方法。系统利用A/D器件对信号进行滤波、放大、差分转换和模数转换,利用FPGA设计内部模块和时钟信号进行电路控制及实现数据缓存、数据传递等功能,由高速DSP芯片核心控制,对采样数据进行实时处理。系统能实现24位高分辨率、宽动态范围的信号数据采集与高速实时处理,可用于电压、电流、温度等参量的采集系统中。     

峰值电流模升压转换器的动态斜坡补偿电路设计

基于HHNEC 0.35 μm BCD工艺设计了一种应用于峰值电流模升压转换器的动态斜坡补偿电路.该电路能够跟随输入输出信号变化,相应给出适当的补偿量,从而避免了常规斜坡补偿所带来的系统带载能力低及瞬态响应慢等问题.经Cadence Spectre验证,该电路能够达到设计要求.     

动态环境下集装箱码头堆场出口箱箱位分配建模与算法研究

箱位分配是集装箱码头运作优化管理的关键问题.针对出口箱交箱时间的动态不确定性,提出两级调度策略,将出口箱位分配问题分解为贝位分配和贝内具体箱位分配,分别建立规划模型优化龙门吊大车行使距离和翻箱量,并针对两级调度策略特点分别设计开发基于禁忌搜索的求解算法.模拟实验表明,所提出的方法能够适应动态条件变化,改善调度效果,并在合理时间内获得满意解.     

事务控制的面向服务系统的动态更新协调

就面向服务的分布式系统中多服务动态更新的协调问题,提出基于事务控制的更新协调策略,包括安全更新时机的选择策略、使用2PC(two-phase-commit)协调多服务更新的控制策略.根据更新实施的各步操作时间开销,提出分别采用更新短事务控制基本更新操作(包括创建服务实例、顺序实施运行时状态转换、重定向服务请求和新服务的...     

基于压力式光纤液位传感器的变压器油高度监测系统

针对传统电力变压器绝缘油位测量的局限性,提出一种压力式光纤液位传感器的变压器绝缘油位监测系统.系统采用压力式光纤液位传感器作为绝缘油位的传感器件,该传感器对光源强度变化、光纤传输过程中的光功率损耗具有光强起伏补偿功能;以数字信号处理器TMS320F2812为处理和控制核心,实现对变压器油位的无人实时在线监测.分析了油位...     

融合遗传算法和蚁群算法动态网格任务调度算法研究

网格计算是当今计算机科学领域最新兴起的一项有很高学术价值和应用价值的研究课题。未来互联网的发展方向是将网络中众多闲置的计算资源、存储资源以及科学仪器等可用资源充分合理的加以利用。如何高效地使用网格资源,即网格调度问题也随之成为研究的重点,虽然在传统的分布式并行计算中有很多成熟的任务调度算法,但由于网格的新特性,使得必须研究新的算法来解决一些新出现的问题,如调度问题的NP安全性,调度算法的高效性,资源的异构性以及资源分配决策的并行性和分布性等。     

基于混合逻辑动态的列车运行调度模型

通过对列车运行调度问题的分析,指出列车运行过程中存在正常事件、客观事件和主观事件三种类型事件,调度的本质是主观事件通过改变列车的运行速度来克服客观事件对列车造成的影响,是典型的混杂系统.在考虑车站股道约束和区间容量两个约束条件的基础上,采用混合逻辑动态理论建立了列车运行调度模型,仿真结果表明了模型的有效性.