一种全面高效的HPCS监控体系*

分析了以超级计算中心联想深腾6800为主的HPCS监控需求,比较了大量的监控实现技术,给出监控系统评估特征和指标,提出了一种集系统、性能、应用程序、进程监控于一体的改进策略,讨论了利用信息流水、过滤、双重传输模式减少监控数据传输量,减轻监控资源消耗,提高综合监控的性能和效率.     

不确定离散系统的鲁棒Gl2滤波器设计

对于凸多面体不确定离散系统,研究了满足误差估计系统鲁棒稳定且满足一定Gl₂性能指标的线性全阶稳定滤波器设计方法.分别给出了确定性和不确定性离散系统具有Gl₂性能的线性矩阵不等式（linear matrix inequality, LMI)充要条件和充分条件.在此基础上,通过使用滤波器参数化方法,分别推导出了以LMI描述的确定性和不确定性系统的Gl₂滤波器存在的充要条件和充分条件,进而可以使用LMI凸优化程序求解滤波器.通过对算例的计算,结果表明,在噪声信号为独立范数有界情况下,鲁棒Gl₂滤波比H_∞滤波具有更少的保守性.     

基于SHIBSS方法和数据优选的系统侧谐波阻抗估算方法

针对盲源分离类方法和传统数据筛选方法的不足,提出一种基于盲源分离的移位阻断(SHIBSS)方法和数据优选的系统谐波阻抗估计方法,对公共连接点处的谐波电压和谐波电流的采样数据采用SHIBSS方法分离出系统侧和用户侧谐波发射电流并计算谐波阻抗;针对谐波阻抗筛选步骤,证实了传统数据筛选方法具有失效率高的问题,提出依据数据优选法辨识系统侧谐波阻抗最优解的方法.仿真分析结果表明,与波动量法、线性回归类常用谐波阻抗估计方法及盲源分离类方法中应用较广泛的快速独立分量分析法相比,SHIBSS方法具有更高的估算精度,数据优选方法克服了传统数据筛选法存在的高失效率的问题,所提系统侧谐波阻抗估算方法具有较高的估计精度.     

浅议降低脉冲袋式除尘器运行费用的几点措施

脉冲袋式除尘器,因其具有良好的清灰效果,并可在较高的过滤风速下稳定运行,因而在袋式除尘器中,占有极其重要的地位。本文介绍了如何降低脉冲袋式除尘器的运行费用,并提出了相应的措施及其在设计中应注意的问题。     

基于小波变换的超声信号自适应消噪方法研究

超声检测中，特定的缺陷回波信号一般都有一定的相关性，因而可利用自适应噪声抵消来增强缺陷回波信号。针对最小均方（LMS）算法自适应噪声抵消的缺点，提出了基于小波变换的自适应噪声抵消方法，通过Matlab软件将该算法应用于超声缺陷信号的仿真处理。结果表明，该算法大大提高了缺陷回波信号的信噪比，且具有较高的缺陷定位精度和纵向分辨率。     

Unscented Kalman filter with advanced adaptation of scaling parameter

The paper deals with state estimation of the nonlinear stochastic systems by means of the unscented Kalman filter with a focus on specification of the σ$\sigma$-points. Their position is influenced by two design parameters—the scaling parameter determining the spread of the σ$\sigma$-points and a covariance matrix decomposition determining rotation of the σ$\sigma$-points. In this paper, a choice of the scaling parameter is analyzed. It is shown that considering other values than the standard choice may lead to increased quality of the estimate, especially if the scaling parameter is adapted. Several different criteria for the adaptation are proposed and techniques to reduce computational costs of the adaptation are developed. The proposed algorithm of the unscented Kalman filter with advanced adaptation of the scaling parameter is illustrated in a numerical example.     

A 5 GHz LC-VCO frequency synthesizer for unlicensed band of WiMAX

This paper presents a low power and low phase noise CMOS integer-N frequency synthesizer based on the charge-pump Phase Locked Loop (PLL) topology. The frequency synthesizer can be used for IEEE 802.16 unlicensed band of WiMAX (World Interoperability for Microwave Access). The operation frequency of the proposed design is ranged from 5.13 to 5.22 GHz. The proposed Voltage-Controlled Oscillator (VCO) achieves low power consumption and low phase noise. The high speed divider is implemented by an optimal extended true single phase clock (E-TSPC) prescaler. It can achieve higher operating frequency and lower power consumption. A new frequency divider is also proposed to eliminate the hardware overhead of the S counter in the conventional programmable divider. The proposed frequency synthesizer consists of a phase-frequency detector (PFD), a charge pump, a low-pass loop filter, a VCO, and a frequency divider. The simulated phase noise of the proposed VCO is −121.6 dBc/Hz at 1 MHz offset from the carrier frequency. The proposed frequency synthesizer consumes 13.1 mW. The chip with an area of 1.048 × 1.076 mm² is fabricated in a TSMC 0.18 μm CMOS 1P6M technology process.     

Leveraging clustering approaches to solve the gray-sheep users problem in recommender systems

Recommender systems apply data mining and machine learning techniques for filtering unseen information and can predict whether a user would like a given item. This paper focuses on gray-sheep users problem responsible for the increased error rate in collaborative filtering based recommender systems. This paper makes the following contributions: we show that (1) the presence of gray-sheep users can affect the performance – accuracy and coverage – of the collaborative filtering based algorithms, depending on the data sparsity and distribution; (2) gray-sheep users can be identified using clustering algorithms in offline fashion, where the similarity threshold to isolate these users from the rest of community can be found empirically. We propose various improved centroid selection approaches and distance measures for the K-means clustering algorithm; (3) content-based profile of gray-sheep users can be used for making accurate recommendations. We offer a hybrid recommendation algorithm to make reliable recommendations for gray-sheep users. To the best of our knowledge, this is the first attempt to propose a formal solution for gray-sheep users problem. By extensive experimental results on two different datasets (MovieLens and community of movie fans in the FilmTrust website), we showed that the proposed approach reduces the recommendation error rate for the gray-sheep users while maintaining reasonable computational performance.     

结合矩阵分解的混合型社会化推荐算法

推荐系统是用来解决当今时代信息过载的重要工具。随着在线社交网络的出现和普及,一些基于网络推荐算法研究的出现,已经引起研究者的广泛关注。信任是社会网络中的重要信息之一,通常用来改进基于社交网络的推荐系统,然而,大多数信任感知的推荐系统忽略了用户有不同行为偏好在不同的兴趣域;本文不仅考虑了用户间特定域信任网络,并且结合推荐项目之间特征属性信息,提出了一种新型社会化推荐算法(H-PMF)。实验表明,H-PMF算法在评分误差和推荐精度上都取得了更好的效果。     

基于间歇测量的状态估计稳定性和精度研究*

针对分布式控制系统状态估计过程出现的测量值丢失问题,本文量化分析测量值丢失对估计稳定性和精度的影响。首先,根据随机测量模型重新推导带测量值丢失的卡尔曼滤波器,得到估计误差协方差迭代式。然后,将随机误差协方差迭代式建模为修正的黎卡提微分方程,提出了估计稳定性和精度分析方法。最后,列举不同的系统实例,证明临界包到达率的存在性,当测量值到达率大于临界值时,平均误差协方差从发散过渡到有界,进而得到估计精度与包达率之间的函数关系。