基于时序上下文的视频场景分类

以传统的词袋模型为基础,根据相邻镜头关键帧之间具有相关性的特点提出了一种用于视频场景分类的模型。将视频片段进行分割,提取关键帧,对关键帧图像归一化。将关键帧图像作为图像块以时序关系合成新图像,提取新图像的SIFT特征及HSV颜色特征,将图像的SIFT特征及HSV颜色特征数据映射到希尔伯特空间。通过多核学习,选取合适的核函数组对每个图像进行训练,得到分类模型。通过对多种视频进行实验,实验结果表明,该方法在视频场景分类中能取得很好的效果。     

FAST LINEAR ESTIMATION METHODS FOR VECTOR AUTOREGRESSIVE MOVING-AVERAGE MODELS

Abstract. Three linear methods for estimating parameter values of vector auto-regressive moving-average (VARMA) models which are in general at least an order of magnitude faster than maximum likelihood estimation are developed in this paper. Simulation results for different model structures with varying numbers of component series and observations suggest that the accuracy of these procedures is in most cases comparable with maximum likelihood estimation. Procedures for estimating parameter standard error are also discussed and used for identification of nonzero elements in the VARMA polynomial structures. These methods can also be used to establish the order of the VARMA structure. We note, however, that the primary purpose of these estimates is to generate initial estimates for the nonzero parameters in order to reduce subsequent computational time of more efficient estimation procedures such as exact maximum likelihood.     

动态三螺杆挤出机制备热塑性硫化胶的研究

对比分析了动态热塑性硫化胶(TPV)的加工设备,着重介绍了附加振动力场的三螺杆反应挤出机的结构特点以及利用该机进行三元乙丙橡胶/聚丙烯(EPDM/PP)的动态全硫化,对制品的物理力学性能和微观结构分别进行了测试分析和电镜扫描。结果表明,振动力场作用下EPDM/PP共混体系反应挤出动态硫化加工可有效地实现动态硫化反应、硫化橡胶的粉碎和分散以及相态反转,振动力场的作用明显提高了TPV性能。     

Bayesian Model Uncertainty In Smooth Transition Autoregressions

Abstract. In this paper, we propose a fully Bayesian approach to the special class of nonlinear time‐series models called the logistic smooth transition autoregressive (LSTAR) model. Initially, a Gibbs sampler is proposed for the LSTAR where the lag length, k, is kept fixed. Then, uncertainty about k is taken into account and a novel reversible jump Markov Chain Monte Carlo (RJMCMC) algorithm is proposed. We compared our RJMCMC algorithm with well‐known information criteria, such as the Akaikes? information criteria, the Bayesian information criteria (BIC) and the deviance information criteria. Our methodology is extensively studied against simulated and real‐time series.     

一种关于模糊时间序列模型论域划分的多尺度比率算法

针对模糊时间序列研究中比率划分论域方法存在对非均匀数据划分效果不理想的缺陷, 提出一种基于模糊C 均值聚类(FCM) 算法的多尺度比率划分论域的方法. 首先利用FCM算法对样本数据进行分类; 然后计算各类数据的平均相对误差, 并基于各类的平均误差划分论域, 产生非等间隔的多尺度论域划分方法; 最后, 通过算例表明了多尺度比率论域划分方法的有效性.     

REVERSED RESIDUALS IN AUTOREGRESSIVE TIME SERIES ANALYSIS

Abstract. Both linear and non-linear time series can have directional features which can be used to enhance the modelling and investigation of linear or non-linear autoregressive statistical models. For this purpose, reversed p th-order residuals are introduced. Cross-correlations of residuals and squared reversed residuals allow extensions of current model identification ideas. Quadratic types of partial autocorrelation functions are introduced to assess dependence associated with non-linear models which nevertheless have linear autoregressive correlation structures. The use of these residuals and their cross-correlation functions is exemplified empirically on some deseasonalized river flow data for which a first-order autoregressive model is a satisfactory second-order fit. Parallel theoretical computations are undertaken for the non-linear first-order random coefficient autoregressive model and comparisons are made. While the data are shown to be strongly non-linear, their correlational signatures are found to be convincingly different from those of a first-order autoregressive model with random coefficients.     

单螺杆挤出机生产率精确控制的研究

研究了单螺杆挤出机生产率的精确控制问题。首先建立了被控对象的数学模型，并分析了被控对象的特性。然后通过对控制过程进行仿真，得出了时间滞后是影响控制质量的最主要因素这一结论。要克服时间滞后的影响，单一的PID反馈控制不能解决问题，因此提出了前馈与反馈相结合用于生产率控制的控制方法，并证明了即使不太精确的前馈环节也能较好地发挥削弱生产率波动的作用。     

基于改进符号化度量方法的机场噪声异常检测

机场噪声中的异常情况拥有很大价值,利用它能够及时完善飞机和机场的设备。结合机场噪声数据的特点,对上述问题进行研究并提出一种基于改进的符号化聚集近似(Symbolic Aggregate Approximation,SAX)相似性度量的单监测点的时间序列异常检测方法。其运用相似性度量方法计算出度量结果,再运用k近邻异常检测方法进行异常发现,最后发现异常时间段。该方法在理论验证可行性之后在某机场的实测数据中进行应用,取得了良好的效果。     

新型螺杆挤出机固体输送理论的研究

介绍了一种嵌套式新型螺杆挤出机。在固体输送段对内螺杆的两种等效情况下固体塞的运动和受力作了深入分析。理论上证明了这两种情况下的固体输送机理与外螺杆的情况相同,均建立在固体摩擦输送机理基础之上;讨论了牵引角、摩擦因数和螺纹升角对上述三种情况固体输送流率的影响。结果表明,螺杆旋转机筒静止和螺杆静止机筒旋转两种情况下固体输送流率相差不大,而螺杆机筒同时旋转情况下的固体输送流率远大于其他两种情况。增大牵引角、降低螺杆表面粗糙度和提高机筒内表面的摩擦因数均有助于提高固体输送流率。螺杆旋转机筒静止和螺杆静止机筒旋转这两种情况下最佳螺旋角均为17°左右,而螺杆机筒同时旋转情况下最佳螺旋角为15°左右。     

MULTIVARIATE WALSH-FOURIER ANALYSIS

Abstract. In this paper we establish a statistical methodology for the spectral analysis of stationary multivariate time series via the Walsh-Fourier transform. Theoretical results pertaining to the definition and estimation of the Walsh-Fourier spectral matrix and functions of that matrix including cross-spectra, coherency and phase are given. An example of the statistical techniques developed in this paper is given; in particular, the methodologies are applied to neonatal sleep data collected from a study of the effect of maternal substance use during pregnancy.