On accelerating sequential procedures for estimating exponential populations

In this study, we accelerate the purely sequential procedure due to Anscombe(1953), Chow and Robbins(1965) to reduce the number of sampling operations required to carry out the estimation process. The method is proposed while estimating the location parameter(s) of the exponential distribution(s). We also develop theory for the asymptotic characteristic of the associated stopping variables. Our findings are applicable to both point as well as confidence interval estimation problems. Other interesting results are also given.     

A comment on sample size calculations for binomial confidence intervals

In this article we examine sample size calculations for a binomial proportion based on the confidence interval width of the Agresti–Coull, Wald and Wilson Score intervals. We pointed out that the commonly used methods based on known and fixed standard errors cannot guarantee the desired confidence interval width given a hypothesized proportion. Therefore, a new adjusted sample size calculation method was introduced, which is based on the conditional expectation of the width of the confidence interval given the hypothesized proportion. With the reduced sample size, the coverage probability can still maintain at the nominal level and is very competitive to the converge probability for the original sample size.     

Confidence intervals for estimating the population signal-to-noise ratio: a simulation study

This paper considered several confidence intervals for estimating the population signal-to-noise ratio based on parametric, non-parametric and modified methods. A simulation study has been conducted to compare the performance of the interval estimators under both symmetric and skewed distributions. We reported coverage probability and average width of the interval estimators. Based on the simulation study, we observed that some of our proposed interval estimators are performing better in the sense of smaller width and coverage probability and have been recommended for the researchers.     

CORRECTING FOR KURTOSIS IN DENSITY ESTIMATION

Using a global window width kernel estimator to estimate an approximately symmetric probability density with high kurtosis usually leads to poor estimation because good estimation of the peak of the distribution leads to unsatisfactory estimation of the tails and vice versa. The technique proposed corrects for kurtosis via a transformation of the data before using a global window width kernel estimator. The transformation depends on a “generalised smoothing parameter” consisting of two real-valued parameters and a window width parameter which can be selected either by a simple graphical method or, for a completely data-driven implementation, by minimising an estimate of mean integrated squared error. Examples of real and simulated data demonstrate the effectiveness of this approach, which appears suitable for a wide range of symmetric, unimodal densities. Its performance is similar to ordinary kernel estimation in situations where the latter is effective, e.g. Gaussian densities. For densities like the Cauchy where ordinary kernel estimation is not satisfactory, our methodology offers a substantial improvement.     

PWPM信号的功率谱研究

对脉冲宽度、位置联合调制(pulse width and position modulation)简称 PWPM 方式的随机信号序列功率谱进行了研究,文献[1]的理论结果显示 PWPM 随机信号序列功率谱中存在符号(symbol)同步信号离散谱成分,这有利于在接收端正确接收 PWPM 信号.用计算机模拟估计了 PWPM 随机信号序列的功率谱.其结果也表明了 symbol 同步信号的存在.     

基于MATLAB仿真和单片机控制的直流脉宽调速系统

阐述了基于MATLAB仿真和单片机控制的数字直流脉宽调速系统,详细介绍了SIMULINK仿真过程和单片机控制系统的组成以及实现方法。     

PWM在合成语音输出电路中的应用

基于采用权电流D/A方式实现合成语音输出方式有集成电阻离散性大、开关的非线性,以及功耗高等缺点,提出了利用脉冲宽度调制(PWM)技术的方法将数字语音信号直接转换为脉冲宽度调制波,并通过低通滤波器生成模拟语音信号。PWM语音输出方式相对一般的DAC语音输出方式具有功耗小、工艺适应能力强、设计可靠等优点,并且PWM语音输出方式已经成功应用于语音合成芯片中,输出合成语音质量良好。     

The Clustering of Categorical Data: A Comparison of a Model-based and a Distance-based Approach

For clustering multivariate categorical data, a latent class model-based approach (LCC) with local independence is compared with a distance-based approach, namely partitioning around medoids (PAM). A comprehensive simulation study was evaluated by both a model-based as well as a distance-based criterion. LCC was better according to the model-based criterion and PAM was sometimes better according to the distance-based criterion. However, LCC had an overall good and sometimes better distance-based performance as PAM, although this was not the case in a real data set on tribal art items.     

新生英语词汇量历时状况调查与分析

词汇量调查与研究在中国已为许多专家、教师所重视,但所做调研多数为共时调查,历时状况的调查不多。历时状况调查可了解学习者词汇量一个时期的稳定水平。为此,笔者对北航2001级和2002级非英语专业本科生在入学后立即进行词汇量测试,对受试总词汇量、中学阶段词汇量和超出中学教纲而在大学英语四级词汇范围内的词汇的识别情况进行了讨论与分析。并根据统计结果对教学安排提出了参考意见。     

Multivariate Real-Time Signal Extraction by a Robust Adaptive Regression Filter

We propose a new regression-based filter for extracting signals online from multivariate high frequency time series. It separates relevant signals of several variables from noise and (multivariate) outliers.

Unlike parallel univariate filters, the new procedure takes into account the local covariance structure between the single time series components. It is based on high-breakdown estimates, which makes it robust against (patches of) outliers in one or several of the components as well as against outliers with respect to the multivariate covariance structure. Moreover, the trade-off problem between bias and variance for the optimal choice of the window width is approached by choosing the size of the window adaptively, depending on the current data situation.

Furthermore, we present an advanced algorithm of our filtering procedure that includes the replacement of missing observations in real time. Thus, the new procedure can be applied in online-monitoring practice. Applications to physiological time series from intensive care show the practical effect of the proposed filtering technique.