延迟离散Hopfield-型网络广义异步收敛性分析

给出了延迟离散Hopfield -型神经网络的收敛性定理。在广义异步运行方式下 ,证明了对称连接权阵 (只要w0 对称 )条件下的收敛性定理 ,推广了已有的延迟离散Hopfield -型神经网络的收敛性结果 ,表明网络收敛滞后于能量函数收敛最多 2n 1步。最后给出了能量函数的极大值点与延迟离散Hopfield -型神经网络的稳定态的关系。     

HARMLESS DELAYS FOR UNIFORM PERSISTENCE

1. IntroductionA number of models in ecology can be formulated as systems of differential equations withtime delays. One of the most important problems for this type of systems is to analyze theeffect of time delays on the stability of the systems. This has been done in many papers. In[1], it is shown that if a time delay is incorporated into the resource limitation of the logisticequation, then it will destabilize the system. In [2]--[4], criteria are established under which anequilibrium of…     

含区间参数的战场资源动态调度模型及算法

战场资源调度是作战指挥领域研究的热点.首先描述了战场资源调度问题,分析了战场资源动态调度需求,在此基础上建立了包含区间参数的战场资源动态调度模型.然后设计了三种不同的贪心策略,分别为基本贪心策略、双重贪心策略和一致贪心策略,提出了模型求解的混合贪心算法.最后结合联合作战算例进行了仿真验证,结果表明本文方法可行优越,能应用于不确定性的战场环境中.     

动态惩罚机制下互联网金融平台行为及监管策略的演化博弈分析

运用演化博弈理论研究了互联网金融平台行为及监管策略的博弈演化过程,系统考察了互联网金融平台行为及监管博弈过程的影响因素,并重点对固定惩罚机制和动态惩罚机制下互联网金融平台行为及其监管策略博弈均衡进行了比较.研究表明,固定惩罚机制下,互联网金融平台和金融监管机构的博弈过程不能达到稳定的均衡状态,两个群体的行为呈现周期模式.动态惩罚机制下,互联网金融平台和金融监管机构间的博弈演化轨迹呈螺旋收敛的趋势;互联网金融平台的"自律"的初始概率不同,其随时间演化收敛到不同的均衡值;提高最重惩罚度上限,互联网金融平台选择"自律"行为策略的概率增加.     

考虑多因素扰动的项目关键链缓冲区间设置及控制模型

项目规划及执行过程中极易出现不确定性,故需对项目关键链缓冲区间进行动态调整以适应项目任务关系变化.针对项目计划关键链缓冲区间设置及调整控制问题,本文提出了一种考虑多因素扰动的缓冲设置及调整控制联动模型.项目初始缓冲设置充分考虑项目工序安全工期、网络复杂程度及资源紧张程度等因素影响,项目执行过程中将缓冲/资源绩效指数与Bayes估计相结合,通过对Weibull分布参数估计实现缓冲信息的递阶转换,提升对缓冲使用的控制能力,最后通过实例验证所提方法与控制模型的有效性.     

Models of Choosing the Financial Compensation Strategy for Flight Delay

At present, most airlines adopted generally the same amount of compensa- tion strategy when needing to provide financial compensation to all flight delay passengers. However, due to the existence of differences in travel time value, ticket fare, as well as the expectation of compensation for flight delays, the gap between the effect of same amount of compensation and many passengers＇ （especially the high-value ones） expectations is large, it results in that airlines need to pay higher cost of compensation, but the total effect of compensation for passengers are not better. This paper advanced four financial com- pensation strategies for flight delays, summarized their own characteristics, and took into account the interests of both airlines and passengers, built the optimization models of the four financial compensation strategies under the restriction of the airline＇s compensation cost and on the goal of the maximum total effectiveness of the financial compensation to all passengers. Finally, based on the specific circumstances of the flight delays, the paper discussed the method for airline to choose the optimal financial compensation strategy through solving four models and comparing the compensation effectiveness.     

求解0-1动态优化问题的双概率原对偶遗传算法

在原对偶遗传算法(PDGA)的基础上,提出一种双概率原对偶遗传算法(DPPDGA).引入弱势基因位值与强势基因位值的概念,对二者赋予不同的对偶映射概率,并对两个对偶概率进行适应性调整.比较原始算法,改进算法使种群具有更理想的多样性,并利于种群较快地收敛到满意解.仿真结果表明,该算法在0-1动态优化问题的求解中具有更好的性能.     

基于飞行体间精确测距的动态相对定位方法

飞行体间的精确相对定位是实现飞行体协同工作的重要技术基础。提出了一种将飞行体惯导信息与相对距离测量信息相结合、实现两飞行体间精确动态相对定位的算法。首先利用较为精确的相对距离测量信息对两飞行体惯导系统的相对误差进行单次修正,提高了两飞行体间的单次相对定位精度。然后,利用相对距离信息进行相对机动状态的检测,并根据检测结果对状态滤波模型进行选择和切换,实现飞行体间的动态相对定位。仿真结果表明,本算法具有较高的相对定位精度和稳定性。     

Robust H∞ filtering for discrete-time systems with Markovian switching and time-delays

The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with modedependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.     

基于水平集方法的动态目标跟踪路径最优仿真

两移动平面运动体因有各自的智能控制器,因此当它们在跟踪控制时,双方必然及时根据对方的策略改变各自的控制策略(方向和速度大小),来达到一种真正的双边最优(主动跟踪者最短时间的追上被跟踪者,而被跟踪者最大化时间避免被追上).首先将平面上任意运动体简化成带速度和加速度的质点,然后利用追逃微分对策理论建立起此跟踪路径最优问题的哈密顿-雅可比-贝儿曼偏微分数学模型.对这种双边极值的难点问题,提出一种水平集数值求解方法.并利用水平集的偏微分方程与哈密顿-雅可比-贝儿曼偏微分方程结构相似性得到水平集的速度函数.对一平面上两无人驾驶飞机的动态跟踪双方进行仿真,仿真编程简单,解决了双边极值的求解.