一种适用于超宽带脉冲信号检测的改进CUSUM算法

将最快检测技术应用于超宽带脉冲信号检测中,具体采用改进的CUSUM(Cumulative Sum)算法来检测超宽带脉冲信号。首先分析了经过多径信道衰减后的超宽带脉冲信号概率分布特性,进一步提出了适用于超宽带脉冲信号检测的改进CUSUM算法。理论分析和仿真证明了所提改进算法性能优越且实现复杂度低。该算法克服了块检测算法的信噪比门限效应,且具有最优的检测延迟性能,相同虚警限制下其检测性能明显优于能量检测算法。     

Structural breaks in time series

This paper gives an account of some of the recent work on structural breaks in time series models. In particular, we show how procedures based on the popular cumulative sum, CUSUM, statistics can be modified to work also for data exhibiting serial dependence. Both structural breaks in the unconditional and conditional mean as well as in the variance and covariance/correlation structure are covered. CUSUM procedures are nonparametric by design. If the data allows for parametric modeling, we demonstrate how likelihood approaches may be utilized to recover structural breaks. The estimation of multiple structural breaks is discussed. Furthermore, we cover how one can disentangle structural breaks (in the mean and/or the variance) on one hand and long memory or unit roots on the other. Several new lines of research are briefly mentioned.     

An Efficient Optimized Handover in Cognitive Radio Networks Using Cooperative Spectrum Sensing

Cognitive radio systems necessitate the incorporation of cooperative spectrum sensing among cognitive users to increase the reliability of detection. We have found that cooperative spectrum sensing is not only advantageous, but is also essential to avoid interference with any primary users. Interference by licensed users becomes a chief concern and issue, which affects primary as well as secondary users leading to restrictions in spectrum sensing in cognitive radios. When the number of cognitive users increases, the overheads of the systems, which are meant to report the sensing results to the common receiver, which becomes massive. When the spectrum, which is in use becomes unavailable or when the licensed user takes the allocated band, these networks have the capability of changing their operating frequencies. In addition, cognitive radio networks are seen to have the unique capability of sensing the spectrum range and detecting any spectrum, which has been left underutilized. Further this capability of recognizing the spectrum range based on the dimensions detected, allows for determination of the band, which may be utilized. The main objective of this paper is to analyze the cognitive radio’s spectrum sensing ability and evolving a self-configured system with dynamic intelligence networks without causing any interference to the primary user. The paper also brings focus to the quantitative analysis of the two spectrum sensing techniques namely; Energy Detection and Band Limited White Noise Detection. The estimation technique for detecting spectrum noise is based on the detection of probability and probability of false alarms at different Signal-to-Noise Ratio (SNR) levels using Additive White Gaussian Noise signal (AWGN). The efficiency of the proposed Cooperative CUSUM spectrum sensing algorithm performs better than existing optimal rules based on a single observation spectrum sensing techniques under cooperative networks.     

基于多尺度估计理论的晶圆减薄工艺方差变化检测方法

晶圆减薄工艺是伴随芯片堆叠技术的发展而出现的新制造过程,其制造质量直接关系最终产品成品率。文章以堆叠芯片晶圆减薄工艺质量参数为研究对象,拟建立监控晶圆减薄工艺质量的完整方法。首先,以该道生产工序质量参数序列建立自回归滑动平均模型,用于表达该道生产工序的质量特征变化。然后,在此模型的基础上,使用多尺度估计理论对该模型进行滤波分解处理,获得质量参数时间序列的高频信号,提取该道质量变异的方差变化。最终,使用统计学上的累积和控制图对质量变异信号进行诊断分析,根据工序方差变化的起始位置,提前发现系统可能存在的质量变坏趋势。经试验数据验证,相比传统的检验方法,该方法有95%的概率可以提前预测产品质量发生变化。     

相依序列均值和方差变点的估计

通过建立统计模型,构造均值、方差变点位置的CUSUM型估计量,研究线性相依序列均值方差同时存在变点的估计问题.考虑均值变点对方差变点的影响,通过均值变点估计量的收敛速度,在均值及均值变点已知与未知两种情况下分别分析方差变点问题,推导出方差变点估计量的收敛速度.     

累积和控制图与休哈特控制图联合应用方法

通过休哈特控制图中的单值控制图、均值控制图和极差控制图与累积和控制图（CUSUM图）进行比较分析,虽然CUSUM图对过程发生的小偏移较灵敏,但在某些情况下休哈特图比CUSUM图能更快地对生产过程异常作出报警.在此研究的基础上,提出了联合应用累积和控制图与休哈特控制图的观点,以尽快发现生产过程的异常波动.     

独立序列均值与方差变点的累积和估计及应用

产品生产加工过程中, 反映产品质量参数的均值和方差都有可能出现异常波动, 及时发现质量异常波动, 对于控制产品质量十分重要. 在工业生产、通信工程等领域中独立序列有广泛应用背景. 本文研究了独立序列中均值和方差都存在变点且变点时刻不相同时的变点估计问题, 给出变点时刻的累积和(CUSUM)型估计, 并得到变点估计的收敛速度. 最后将该方法应用于航空发动机管路生产质量控制中和放射医学研究的扫描仪质量控制问题中,模拟结果和实例分析都说明方法的有效性.     

Beyond the Nomogram: Rapid Selection of Parameters for a CUSUM Chart

The cumulative sum chart is widely employed in quality control. These charts are designed to exhibit acceptable average run lengths both when the process is in and out of control. This paper introduces a technique for parameter selection for such a chart for specified average run lengths. It is essentially an updating of the well-known nomogram technique.     

A Note on the Lower-Sided Synthetic Chart for Exponentials

The synthetic control chart for exponential data is discussed and an expression is derived for its average run length, as well as its design parameters. The synthetic control chart for exponentials is shown analytically to be a two-in-a-row rule. This chart is compared with the Shewhart chart for individuals and with the worst-case, lower-sided exponential EWMA and CUSUM charts. While the synthetic control chart for exponentials outperforms the Shewhart chart for individuals, the EWMA and CUSUM charts are shown to be far superior in detecting decreases in the exponential mean.