小波分析在证券分析中的应用

传统股市投资分析中的证券分析方法之一———MACD法 ,利用DIF的移动平均值以确定证券的买卖时机 ,存在着时滞性 ,对非平稳的股市信息分析不能及时、较好地刻画股市的基本变化趋势 .作者根据证券投资理论 ,建立了相应的证券投资分析数学模型 ,根据小波分析多尺度分析能力强的特点 ,利用小波分解提取反映股市基本变化趋势的低频信息 ,改进了传统分析方法 ,建立了改进后的数学模型Ⅲ .该模型求解方便 ,同时与实际模型较好地逼近 ,具有时效性 .此外 ,以路桥建设股票 14 0个交易日的DIF和MACD值作为原始数据 ,用Matlab作为工具进行计算 ,求解模型Ⅲ .结果表明 :与传统分析方法相比 ,从模型Ⅲ中能得到更多的买卖点信息 ,而且价差更大 ,效果显著 ,充分显示了小波分析在股市技术分析中的强大生命力     

高新张铜一路高歌

高新张铜股份有限公司系国家国资委管辖的中国高新投资集团公司控股的中央企业,公司自1999年成立以来,现已成为中国最大的环保铜水管生产基地、中国最大的空调制冷铜管生产基地,是国家重点高新技术企业,被誉为民族有色工业的一面旗帜.     

基于二分法迭代的频谱感知节能优化策略

针对认知无线电(CR)系统中频谱感知技术能量效率低的问题,提出了一种基于二分法迭代寻优的联合优化算法。该算法通过联合传输功率与感知时隙进行优化,最大化地提高了CR系统的能量效率,并且在针对优化参数ξ的寻优过程中,使用了二分法与迭代算法结合的寻优方法。通过理论分析,与其他类似算法相比,该算法的寻优速度更快,算法复杂度更低,函数收敛速度更快,实际应用的可扩展性更强。数值仿真分析结果表明,在保证检测性能的前提下,提出的算法能够很好地解决能效的最优化问题,在恒定检测概率Pd=0.9和Pd=0.7条件下,所提出算法的能耗开销均低于其他算法,在系统吞吐量中所提出算法均优于其他算法,为CR系统的发展提供了理论支撑,更加符合未来CR系统的节能发展方向。     

Refractive-diffractive visual system for micro-display of LCOS

One head-mounted display visual system for computer entertainment and three-dimensional display of virtual-reality was achieved, which consists of a hybrid refractive-diffractive eyepiece and a relay reflector. It can be used in micro-display of liquid crystal on silicon (LCOS) diagonal of 18 mm. The whole system has better performance, with 60° field of view, 10 mm exit pupil, 23 mm eye relief, and reduces weight and size.     

聚合物薄膜和纤维的强度及寿命的统计学性质

这本专著是由1999年出版的俄语版《高分子膜的强度和破裂》一书修订和扩充而来的。书中展示了作者在脆性和准脆性断裂的固态高分子方面长期做的理论性和实验研究的结果。作者对各种状况下聚合物断裂的统计学特性进行了综合而详细的研究，包括不同的温度、不同的机械应力、不同表面活性媒质、紫外线和1光照射、化学混合物作用等等各种不同条件下的统计学特性。该研究的关键在于发现了两种主要的强度状态：块体试样的低强度状态和纤维及薄膜的高强度状态。书中详细研究了这两种强度状态下的破裂模型的差别。     

电荷掺杂和杂原子掺杂聚硅烷的比较性理论研究

本文利用GAUSSIAN 03程序包中的密度泛函理论,在B3LYP/6-31G(d)水平下,对聚21硅烷、电荷掺杂的聚21硅烷以及杂原子(硼和磷)掺杂的聚21硅烷进行几何全优化,并对它们的几何结构和自旋密度进行了比较性理论研究.结果表明,电荷掺杂能使聚硅烷的Si—Si键长增长,其极子分布几乎遍及了聚21硅烷的整个链;而杂原子(B、P)的掺杂对聚硅烷的影响主要集中在与B、P原子相邻的Si原子上,极子分布仅局域在B、P原子附近的3~5个原子上.     

Forecasting volatility by means of threshold models

The aim of this paper is to compare the forecasting performance of competing threshold models, in order to capture the asymmetric effect in the volatility. We focus on examining the relative out‐of‐sample forecasting ability of the SETAR‐Threshold GARCH (SETAR‐TGARCH) and the SETAR‐Threshold Stochastic Volatility (SETAR‐THSV) models compared to the GARCH model and Stochastic Volatility (SV) model. However, the main problem in evaluating the predictive ability of volatility models is that the ‘true’ underlying volatility process is not observable and thus a proxy must be defined for the unobservable volatility. For the class of nonlinear state space models (SETAR‐THSV and SV), a modified version of the SIR algorithm has been used to estimate the unknown parameters. The forecasting performance of competing models has been compared for two return time series: IBEX 35 and S&P 500. We explore whether the increase in the complexity of the model implies that its forecasting ability improves. Copyright © 2007 John Wiley & Sons, Ltd.     

Telomeres and meiosis in health and disease

Beyond their role in replication and chromosome end capping, telomeres are also thought to function in meiotic chromosome pairing, meiotic and mitotic chromosome segregation as well as in nuclear organization. Observations in both somatic and meiotic cells suggest that the positioning of telomeres within the nucleus is highly specific and believed to be dependent mainly on telomere interactions with the nuclear envelope either directly or through chromatin interacting proteins. Although little is known about the mechanism of telomere clustering, some studies show that it is an active process. Recent data have suggested a regulatory role for telomere chromatin structure in telomere movement. This review will summarize recent studies on telomere interactions with the nuclear matrix, telomere chromatin structure and factors that modify telomere chromatin structure as related to regulation of telomere movement.     

Weight measurement using image-based pose analysis

Image-based gait analysis as a means of biometric identification has attracted much research attention. Most of the existing methods focus on human identification, posture analysis and movement tracking. There have been few investigations on measuring the carried load based on the carrier＇s gait characteristics by automatic image processing. Nevertheless, this measurement is very useful in a number of applications, such as the study of the carried load on the postural development of children and adolescence. In this paper, we investigate how to automatically estimate the carried weight from a sequence of images. We present a method to extract human gait silhouette based on an observation that humans tend to minimize the energy during motion. We compute several angles of body leaning and determine the relationship of the carried weight, the leaning angles and the centroid location according to a human kinetic study. Our weight determination method has been verified successfully by experiments.