Heterogeneity,nonlinearity and endogenous market volatility

This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. An exogenous noise is introduced to the model with the assumption of IID normal innovations of the fundamental value in order to investigate how noisy dynamics interacts with deterministic process. The market is composed of two typical trader types: the rational fundamentalists and the boundedly rational traders governed by greed and fear. The interaction between noise and deterministic element determines the evolution process of the system as key parameters are changed. The authors find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S&P500 index, such as volatility clustering, fat tails (leptokurtosis), autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. The authors also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.     

Atomic-scale segregation behavior of Sn/Ti and O at Σ3[11¯0](111) grain boundary in niobium

First-principle calculation was performed to illustrate the atomic arrangement and segregation behavior of Sn/Ti and O in View the MathML source grain boundary, and the interaction of oxygen interstitials with Sn/Ti atoms on the grain boundary was studied. The analyses on the segregation energies and geometric positions, and the electron densities show that Sn, Ti and O atoms segregate at the Σ3 grain boundary. And the preferred segregation sites of the impurities at View the MathML source were determined. When Sn segregates at grain boundary plane, the O atom prefers to the bulk-like site and shows no segregation tendency at grain boundary, whereas the segregated Ti atom can slightly enhance oxygen segregation at the grain boundary.     

Compact fiber-optic diode-laser sensor system for wide-dynamic-range relative humidity measurement

A compact fiber-optic diode-laser sensor system for measuring relative humidity is studied. In such a system, a distributed feedback laser lasing near 1877 nm is used as light source while a high-precision Pt resistance as temperature sensor, an accuracy of 0.1% relative-humidity can be achieved. The laser sensor system is able to lock to the absorption peak and calculate the density of water vapor without any additional reference measurements. Using programs built in to the microcontroller unit, the laser system can switch functions between direct measurement at high density and second-harmonic detection at low density. The system can switch between the two modes automatically and work in a wide dynamic range.     

HMCM-56分子筛催化苯酚与异丙醇烷基化反应的研究

研究HMCM-56分子筛上苯酚与异丙醇烷基化反应,探讨了反应条件包括温度,原料配比,催化剂的装填量,空速对催化剂催化性能的影响．通过X射线衍射、研究催化剂的酸性及晶相．得到最佳反应条件：T=220℃,WHSV=3．0h^-1,Catalyst Loading=0．3g,n（IPA）／n（Phenol）=0．8,苯酚的转...     

基于相对误差的线性组合预测研究

在讨论传统的组合预测方法的基础上,对相对误差准则下的线性组合预测进行了研究和推广。分别以"相对误差平方之和最小"、"相对误差之和最小"和"最大相对误差最小"为准则,给出了9个线性组合预测模型,其中有6个线性组合预测模型是新提出的,并且讨论了模型的解法。以美国加州电力日均价为例,给出了9种线性组合预测模型的预测结果,验证了新模型的精确性和优越性。     

基于神经网络威胁判断模型

将神经网络理论应用于防空指挥控制系统中 ,研究了威胁判断模型 ,实例表明该方法是可行的 .     

基于启发式的多机器人SLAM地图融合方法研究

同步定位和地图构建（simultaneous localization and mapping,SLAM）是移动机器人在未知环境中完成地图构建和定位任务的关键技术。针对多机器人SLAM中的地图融合问题,提出一种启发式的搜索方法引导局部地图的重复区域进行地图融合。每个机器人可以在不了解其相对位置的情况下建立局部地图,并将局部地图信息发送至同一工作站中,以局部地图的相似性为判断指标融合得到最优的全局地图。在机器人实物平台上进行验证,结果证明了多机器人SLAM的地图融合算法的有效性和准确性。     

纳米SnO2的制备及电化学性质

以无机盐为前体,采用溶胶-凝胶法制备了纳米SnO₂粉体.用TG-DTA,XRD,SEM等对SnO₂粉末进行了表征.结果表明,采用该法经500 ℃热处理得到的SnO₂超细粉具有良好的四方结构,粒径分布均匀,平均粒径在92 nm左右.将该法制得的SnO2超细粉作为锂离子电池负极材料,可逆容量高达687　mAh·g^-1,而且嵌脱锂电压低(0.2～0.5 V),是一种很有潜力的锂离子电池负极材料.     

Adaptive Control of the Structural Balance for a Class of Complex Dynamical Networks

In social networks, the structural balance is a state of a group of individuals(nodes) with established mutual relationships(connection relationships) between them. It is easy to see that a social network can be described by a complex dynamical network model composed of the nodes subsystem(NS) and the connection relationships subsystem(CS), where the two subsystems are usually coupled with each other. It implies that the dynamic changes of nodes' states may cause the structural balance in CS. However, few papers have discussed the relationship between the structural balance and the specific dynamic changes of the nodes' states. This paper proposes a model of complex dynamical networks, and mainly focuses on the dynamic changes of states in NS which can lead to the structural balance in CS. It is proved that if each state in NS is doing a specific dynamic motion via the controller with the parameter adaptive law, then the CS can track a given structural balance matrix via the effective coupling and the structural balance can be achieved. Such a result can be regarded as an explanation of the relationship between the structural balance and the specific dynamic changes of the nodes' states. Finally, the simulations verify the effectiveness of the proposed method.     

考虑自动驾驶仪动态特性与攻击角约束的模糊自适应动态面末制导律

在大口径舰炮制导炮弹打击近岸机动目标的末制导段,考虑自动驾驶仪二阶动态特性与攻击角约束,基于模糊自适应逼近与动态面控制提出一种末制导律。构建二维弹目相对运动模型,运用扩张状态观测器估计目标加速度。为零化视线角的跟踪误差与视线角速率,采用自适应指数趋近律设计非奇异终端动态面滑模,设计模糊自适应系统逼近变结构项,削弱自动驾驶仪的控制指令抖振。通过Lyapunov第二法证明了闭环系统中视线角的跟踪误差与视线角速率均一致最终有界。仿真实验表明:该制导律使制导炮弹在打击具有不同加速度形式的目标时,均具备较好的末制导性能。