New properties of scalar-field dynamics in an isotropic cosmological model on the brane

We investigate some aspects of the scalar-field dynamics on the brane that differ from the corresponding regimes in standard cosmology. We consider asymptotic solutions near singularity, inflation and rebound conditions, and some features of chaos in the model on the brane. Our results are compared with their analogs in classical cosmology.     

Global chaoticity in the Pythagorean three-body problem

The effects of small changes in the initial conditions of the Pythagorean three-body problem are investigated by computer simulations. This problem consists of three interacting bodies with masses 3, 4 and 5 placed with zero velocities at the apices of a triangle with sides 3, 4 and 5. The final outcome of this motion is that two bodies form a binary and the third body escapes. We attempt to establish regions of the initial positions which give regular and chaotic motions. The vicinity of a small neighbourhood around the standard initial position of each body defines a regular region. Other regular regions also exist. Inside these regions the parameters of the triple systems describing the final outcome change continuously with the initial positions. Outside the regular regions the variations of the parameters are abrupt when the initial conditions change smoothly. Escape takes place after a close triple approach which is very sensitive to the initial conditions. Time-reversed solutions are employed to ensure reliable numerical results and distinguish between predictable and non-predictable motions. Close triple approaches often result in non-predictability, even when using regularization; this introduces fundamental difficulties in establishing chaotic regions.     

Is a chaotic multi‐fractal approach for rainfall possible?

An Erratum has been published for this article in Hydrological Processes 15 (12) 2001, 2381–2382. Applications of the ideas gained from fractal theory to characterize rainfall have been one of the most exciting areas of research in recent times. The studies conducted thus far have nearly unanimously yielded positive evidence regarding the existence of fractal behaviour in rainfall. The studies also revealed the insufficiency of the mono‐fractal approaches to characterizing the rainfall process in time and space and, hence, the necessity for multi‐fractal approaches. The assumption behind multi‐fractal approaches for rainfall is that the variability of the rainfall process could be directly modelled as a stochastic (or random) turbulent cascade process, since such stochastic cascade processes were found to generically yield multi‐fractals. However, it has been observed recently that multi‐fractal approaches might provide positive evidence of a multi‐fractal nature not only in stochastic processes but also in, for example, chaotic processes. The purpose of the present study is to investigate the presence of both chaotic and fractal behaviours in the rainfall process to consider the possibility of using a chaotic multi‐fractal approach for rainfall characterization. For this purpose, daily rainfall data observed at the Leaf River basin in Mississippi are studied, and only temporal analysis is carried out. The autocorrelation function, the power spectrum, the empirical probability distribution function, and the statistical moment scaling function are used as indicators to investigate the presence of fractal, whereas the presence of chaos is investigated by employing the correlation dimension method. The results from the fractal identification methods indicate that the rainfall data exhibit multi‐fractal behaviour. The correlation dimension method yields a low dimension, suggesting the presence of chaotic behaviour. The existence of both multi‐fractal and chaotic behaviours in the rainfall data suggests the possibility of a chaotic multi‐fractal approach for rainfall characterization. Copyright © 2001 John Wiley & Sons, Ltd.     

Report on the dynamical evolution of an axially symmetric quasar model

The role of the angular momentum in the regular or chaotic character of motion in an axially symmetric quasar model is examined. It is found that, for a given value of the critical angular momentumL _zc , there are two values of the mass of the nucleusM _n for which transition from regular to chaotic motion occurs. The [L _zc – M _n ] relationship shows a linear dependence for the time independent model and an exponential dependence for the evolving model. Both cases are explained using theoretical arguments together with some numerical evidence. The evolution of the orbits is studied, as mass is transported from the disk to the nucleus. The results are compared with the outcomes derived for galactic models with massive nuclei.     

智能优化LSSVM算法的混沌时间序列边坡变形预测模型

边坡变形序列存在一定混沌特征,本文将混沌分析方法应用到边坡变形预测中。为解决标准LSSVM模型中惩罚参数和核函数参数因任意给定或经验给定带来的非最优问题,将遗传算法和粒子群算法引入LSSVM模型,根据变形序列建立GA-LSSVM和PSO-LSSVM预测模型,与标准LSSVM混沌预测模型和基于神经网络的混沌预测模型进行比较。结果表明,GA-LSSVM和PSO-LSSVM模型预测中误差分别为0.73 mm和0.77 mm,LSSVM,BP,RBF三种模型中误差分别为0.90 mm,0.80 mm和0.75 mm;因此,本文提出的预测模型用于边坡变形预测比其他几种模型具有更高的精度。     

基于双幂次滑模的多机器人编队控制

本文研究了基于领航跟随法的多机器人系统编队控制问题.首先,基于队形约束,给出跟随者期望的轨迹,将编队问题转化为单个跟随者的轨迹跟踪问题.在此基础上,基于双幂次滑模趋近律,设计了跟随者的线速度和角速度控制器,保证了跟踪误差能够快速收敛到零,从而保证了编队队形的稳定.最后,通过仿真验证了所提方法的有效性.     

混沌蜂群优化的NSST域多光谱与全色图像融合

为有效融合多光谱图像的光谱信息和全色图像的空间细节信息,提出了一种基于混沌蜂群优化和改进脉冲耦合神经网络(PCNN)的非下采样Shearlet变换(NSST)域图像融合方法。首先对多光谱图像进行Intensity-HueSaturation(IHS)变换,全色图像的直方图按照多光谱图像亮度分量的直方图进行匹配;然后分别对多光谱图像的亮度分量和新全色图像进行NSST变换,对低频分量使用改进加权融合算法进行融合,以互信息作为适应度函数,利用混沌蜂群算法找到最优加权系数。对高频分量采用改进脉冲耦合神经网络(PCNN)方法进行融合,再经NSST逆变换和IHS逆变换得到融合图像。本文方法在主观视觉效果和信息熵、光谱扭曲度等客观定量评价指标上优于基于IHS变换、基于非下采样Contourlet变换(NSCT)和非负矩阵分解(NMF)、基于NSCT和PCNN等5种融合方法。本文方法在提升图像空间分辨率的同时,有效地保留了光谱信息。     

������������С��ȥ�������Ԥ��

?纣??????????硢????????????????????????????α???????????????????????????????????????db10С???????????????????????????????е???????????????С???????????????????????????????????????Lyapunov??????????????????ж???????????????????????????????????????з??????????????????????????     

利用混沌粒子群算法确定河流水质模型参数

将混沌寻优思想引入到粒子群优化算法中,提出了混沌粒子群算法,这种方法利用混沌运动的随机性、遍历性和规律性等特性对当前粒子群体中的粒子进行混沌寻优。通过这种处理使得粒子群体的进化速度加快,从而改善了粒子群优化算法摆脱局部极值点的能力,提高了算法的收敛速度和精度。并将混沌粒子群算法应用于求解分析瞬时投放示踪剂情况下的一维河流水团示踪试验数据以及确定河流水质参数的函数优化问题,结果表明,混沌粒子群算法的收敛性能明显优于粒子群优化算法。     

一种基于分数阶傅里叶变换的改进图像加密算法

针对目前基于分数阶傅里叶变换的图像加密算法中存在的不足,设计了一种基于分数阶傅里叶变换和混沌系统的图像加密新算法。图像加密过程分两个步骤：首先将原始图像的分数阶傅里叶变换系数经过双随机相位加密,然后利用混沌系统生成的置乱矩阵对图像进行置乱加密后得到最终的加密图像。方案的安全性依赖于随机相位掩膜、分数阶傅里叶变换阶数以及混沌系统的初始参数。理论分析和模拟实验结果表明该方案具有良好的图像加密效果。