Trends cycles and seasons: Econometric methods of signal extraction

Alternative methods of trend extraction and of seasonal adjustment are described that operate in the time domain and in the frequency domain.

The time-domain methods that are implemented in the TRAMO–SEATS and the STAMP programs are compared. An abbreviated time-domain method of seasonal adjustment that is implemented in the IDEOLOG program is also presented. Finite-sample versions of the Wiener–Kolmogorov filter are described that can be used to implement the methods in a common way.

The frequency-domain method, which is also implemented in the IDEOLOG program, employs an ideal frequency selective filter that depends on identifying the ordinates of the Fourier transform of a detrended data sequence that should lie in the pass band of the filter and those that should lie in its stop band. Filters of this nature can be used both for extracting a low-frequency cyclical component of the data and for extracting the seasonal component.     

最大熵模型的事件分类

提出了一种基于最大熵模型的事件分类方法,该方法能够综合事件表述语句中的触发词信息及各类上下文特征对事件进行分类。对其中的两个关键问题:参数估计、特征模板与特征选择进行了详细论述,采用IIS算法学习模型参数,使用增量选择方法选择特征。应用该方法对人民日报语料中的职务变动、会见、恐怖袭击、法庭宣判、自然灾害五类事件进行了分类实验,结果表明,该方法的分类效果明显优于传统的分类方法。     

语义取象对词义演变的影响——以“牙、齿”为例

词的所指对象依照认知经验会在人的心目中形成一定的心理意象,我们称之为语义取象。通过对牙、齿的词义分析,我们发现:受深层认知因素的制约,两个词即使词汇意义大致相当,但它们在人们认知体系中有不同的意象和各自突显的特征,这深刻影响着词的使用和词义的发展,对词义系统的自我调控与平衡是极有利的。聚焦于词的语义取象,使我们获得了词义分析的新视角,能够为多义词的义域分布和发展趋势提供解释,也为同义词的辨析提供了新思路。     

枇杷皮和芒果皮粗提液抗氧化活性研究

研究了枇杷皮和芒果皮粗提液在卵黄脂蛋白不饱和脂肪酸过氧体系和油脂中的抗氧化活性,并比较了两种粗提液对OH和O-自由基的清除能力,结果表明:枇杷皮和芒果皮粗提液对卵黄脂蛋白不饱和脂肪酸过氧体系和鲜榨花生油均有较强的抗氧化性能,并具有较强的清除两种自由基的能力,其中芒果皮的抗氧化性优于枇杷皮。     

合成孔径雷达图像目标分类研究

基于灰度共生矩阵技术,研究了可用于合成孔径雷达图像分类的灰度共生矩阵中差方差、差熵、对比度、能量、方差等纹理特征量,分析了其特征提取和分类特性。运用类内类间距准则,通过计算图像特征值的类内类间距,得到对合成孔径雷达图像分辨效果较好的纹理特征量,并利用三层BP神经网络进行图像分类,获得了满意的分类结果。     

In the shadow of the coal breaker: cultural extraction and participatory communication in the Anthracite Mining Region

What stories do ruins tell? What is the legacy of the extractive coal industry? When is extraction complete in a single-industry area? Tied to global capital, fuelling the Industrial Revolution on the labour immigrants, the legacy of extraction in the Anthracite Coal-Mining Region in Northeastern Pennsylvania extends into local notions of heritage, memory, community welfare, and place. Tracking (de)industrial life scenes in the Anthracite Coal-Mining Region, this ethnographic work follows traces of the past as they emerge and the day-to-day practices that sustained them noting intensities and flashpoints as they arise in daily life. As a particular flashpoint, Coal Region residents processed the demolition of the ruins of Saint Nicholas Coal Breaker, the last anthracite coal breaker built before 1960 and once the largest coal breaker in the world. Residents rapidly produced and shared digital media of the Breaker with and through a large public digital humanities collaboratory that I created and maintain through an active Facebook page (https://www.facebook.com/AnthraciteCoalRegion) of more than 8000 members and a corresponding website (http://anthracitecoalregion.com). Engaging in community dialogue, participatory communication, and offering critical interpretations, residents wrote accounts about the demolition of the Breaker including its historical and mnemonic relevance, the cultural politics surrounding it, and the ethical dimensions of its extraction from the landscape by a mining company engaged in strip-mining on the surrounding land. These connections and dislocations between situated pasts show affective intensities arising suddenly even though dominant or more official narratives may have overwhelmed them. The sanitizing of the landscape of Saint Nicholas Breaker tries to empty the physical place of the material cultural traces of mining people/mined people to re-extract more coal through strip-mining operations, thereby rendering superfluous the underground miners’ labour by removing the last sign of it - the Breaker - from the landscape.     

Diagnostic Checking of Unobserved-Components Time Series Models

Diagnostic checking of the specification of time series models is normally carried out using the innovations—that is, the one-step-ahead prediction errors. In an unobserved-components model, other sets of residuals are available. These auxiliary residuals are estimators of the disturbances associated with the unobserved components. They can often yield information that is less apparent from the innovations, but they suffer from the disadvantage that they are serially correlated even in a correctly specified model with known parameters. This article shows how the properties of the auxiliary residuals may be obtained, how they are related to each other and to the innovations, and how they can be used to construct test statistics. Applications are presented showing how residuals can be used to detect and distinguish between outliers and structural change.     

线性预测盲源提取算法应用于阵列雷达的分析

通过深入分析阵列雷达的杂波/干扰抑制问题,提出应用基于线性预测的有噪盲源提取算法来提取阵列雷达的回波信号,实现杂波/干扰的同时抑制,最终提高阵列雷达的目标探测能力。在建立逼真的阵列雷达接收信号模型的基础上,通过仿真分析了该算法提取阵列雷达回波的能力和改善阵列雷达的目标探测能力。结果表明,该算法提取雷达回波信号的效果理想,平均相关系数大于0.93;当运动目标的归一化多谱勒频率大于±0.1Hz时,阵列雷达的检测概率接近1,验证了该算法的可行性和有效性。     

晚清报刊摘录转载的实践与中国现代版权制度的建立

摘录转载的引入与普遍实践促进了晚清书刊编辑出版的繁荣，在实践中，出版人及作家发现摘录转载报载文字侵犯了他们的利益，他们于是对报载特定内容的版权保护意识和要求逐渐增强，“不许转载”的呼吁和申明开始在晚清报界流行并成为行业规则，随后获得法律保护。晚清报刊摘录转载的实践促进了报刊文字版权保护的科学化、规范化，为中国现代报刊文字的版权保护行规法令的形成奠定了基础。晚清报刊摘录转载的普及和规范化是认识中国现代版权意识和制度产生和建立的一个不可或缺的视角。     

Single and multiple error state-space models for signal extraction

We compare the results obtained by applying the same signal-extraction procedures to two observationally equivalent state-space forms. The first model has different errors affecting the states and the observations, while the second has a single perturbation term which coincides with the one-step-ahead forecast error. The signals extracted from both forms are very similar but their variances are drastically different, because the states for the single-source error representation collapse to exact values while those coming from the multiple-error model remain uncertain. The implications of this result are discussed both with theoretical arguments and practical examples. We find that single error representations have advantages to compute the likelihood or to adjust for seasonality, while multiple error models are better suited to extract a trend indicator. Building on this analysis, it is natural to adopt a ‘best of both worlds’ approach, which applies each representation to the task in which it has comparative advantage.