Supervised classification of share price trends

Share price trends can be recognized by using data clustering methods. However, the accuracy of these methods may be rather low. This paper presents a novel supervised classification scheme for the recognition and prediction of share price trends. We first produce a smooth time series using zero-phase filtering and singular spectrum analysis from the original share price data. We train pattern classifiers using the classification results of both original and filtered time series and then use these classifiers to predict the future share price trends. Experiment results obtained from both synthetic data and real share prices show that the proposed method is effective and outperforms the well-known K-means clustering algorithm.     

Using anatomical knowledge expressed as fuzzy constraints to segment the heart in CT images

Segmenting the heart in medical images is a challenging and important task for many applications. In particular, segmenting the heart in CT images is very useful for cardiology and oncological applications such as radiotherapy. Although the majority of methods in the literature are designed for ventricle segmentation, there is a real interest in segmenting the heart as a whole in this modality. In this paper, we address this problem and propose an automatic and robust method, based on anatomical knowledge about the heart, in particular its position with respect to the lungs. This knowledge is represented in a fuzzy formalism and it is used both to define a region of interest and to drive the evolution of a deformable model in order to segment the heart inside this region. The proposed method has been applied on non-contrast CT images and the obtained results have been compared to manual segmentations of the heart, showing the good accuracy and high robustness of our approach.     

Retrieving ocean surface current by 4-D variational assimilation of sea surface temperature images

In this article we propose a new method to estimate ocean mesoscale structures of the surface current velocity by processing sea surface satellite images. Assuming that the intensity level can be described by a transport-diffusion equation, the proposed approach is based on variational assimilation of image observations within a simple transport-diffusion model. This approach permits to retrieve the current velocity field from a sequence of satellite images. Results of processing synthetic data and real NOAA-AVHRR satellite images are presented and commented.     

Robust Kalman filtering for uncertain discrete-time systems with probabilistic parameters bounded within a polytope

We consider the problem of finite horizon discrete-time Kalman filtering for systems with parametric uncertainties. Specifically, we consider unknown but deterministic uncertainties where the uncertain parameters are assumed to lie in a convex polyhedron with uniform probability density. The condition and a procedure for the construction of a suboptimal filter that minimizes an expected error covariance over-bound are derived.     

弹体撞击钢板过载信号处理方法

弹体在跌落撞击钢板过程中,弹体上将会叠加非常复杂的震荡信号,这些震荡信号对实际过载信号的提取和分析将造成不可忽视的影响.本文通过将实弹跌落至钢板,采集到弹体在碰撞钢板过程中的过载信号和弹体上的各阶震荡信号,并对这些震荡信号进行频谱分析和ANSYS有限元模态分析,为弹体的碰撞过载数据分析提供了帮助.     

Optimal experimental design and some related control problems

This paper traces the strong relations between experimental design and control, such as the use of optimal inputs to obtain precise parameter estimation in dynamical systems and the introduction of suitably designed perturbations in adaptive control. The mathematical background of optimal experimental design is briefly presented, and the role of experimental design in the asymptotic properties of estimators is emphasized. Although most of the paper concerns parametric models, some results are also presented for statistical learning and prediction with nonparametric models.     

Improved inter-view correlations for low complexity MV-HEVC

The more advanced multi-view extension, MV-HEVC, effectively exploits visual similarities between multi-view videos and enables high compression efficiency. Each view in the multi-view sequence depends on the captured scene, the distance between cameras and recording angles. Increasing the distance between dependent viewpoints generates an inter-view disparity. This impacts the inter-view similarities, affects the disparity estimation and further increases the computational complexity of the MV-HEVC encoder. In this paper, an efficient earlier disparity estimation is proposed for low complexity MV-HEVC. This algorithm is based on reducing the complexity of disparity estimation by eliminating the inter-view offset. Moreover, the inter-view similarities are controlled by considering the reliability of each coding unit size in the search range. This reliability is estimated by reducing the number of searching points within a new limited window. For reliable motion estimation, we further proposed an earlier decision of coding units splitting in the dependent views according to those in the reference views. Experimental results show that the proposed algorithm can achieve an average encoding time saving of 20.37%–40,61% with marginal performance degradation.     

SBS改性沥青超热老化模式下氧化与挥发的贡献机理

利用宏观和微观分析相结合的方法,定量分析了SBS改性沥青超热老化模式下氧化与挥发的贡献机理。通过研究不同老化温度下常规三大指标,DSR流变车辙因子分别在空气氛和高纯氮气氛下老化的衰变规律,并结合傅里叶变换红外光谱微观表征手段,定量计算出SBS改性沥青超热老化过程中氧化与挥发的贡献率,得出SBS改性沥青在超热老化模式下,其老化机理是以SBS分子中的双键被氧化为主要因素,但随着超热老化温度升高,小分子挥发等非氧化因素逐渐成为超热老化的又一主要因素。宏观分析中,从普通老化的163℃到超热老化的198℃,氧化与挥发对SBS改性沥青针入度衰减的贡献率比由6∶4变为1∶1;对延度衰减的贡献率比由7∶3变为1∶1;对车辙因子的贡献率比由24∶1变为2∶1;而红外光谱微观分析中,氧化与挥发对SBS改性沥青超热老化后不饱和双键的衰减贡献率比由7∶3变为1∶1。     

一种快速自适应谱估计算法

通过对梯度格型快速自适应算法的研究,结合最大熵谱外推目前存在的缺点,将梯度格型算法应用于最大熵谱外推中,并将其与伯格算法进行了比较。