1) exponential convergence
指数收敛性
1.
The Exponential Convergence and Boundedness of the Solutions for Functional Differential Equations;
泛函微分方程解的指数收敛性及其有界性
2.
A new design method of nonlinear reduced order state observer is proposed,and the exponential convergence is proved for the proposed state observer.
提出一种非线性降维状态观测器设计方案 ,并从理论上证明了状态观测误差的指数收敛性 。
3.
The paper studies the existence and global exponential convergence of alomost periodic solutions for high-order neural networks involving variable delay by applying the theory of fixed point and differential inequality technique,some new criteria on the existence and global exponential convergence of almost periodic solutions are obtained.
利用不动点理论和微分不等式分析等技巧,研究了变时滞高阶神经网络概周期解存在性与全局指数收敛性,并且给出了一些新的判别准则。
2) global exponential convergence
全局指数收敛性
1.
Existence and global exponential convergence of almost periodic solution for competitive neural networks with varying time-delays and different time-scales;
具有不同时间尺度的变时滞竞争神经网络概周期解的存在性和全局指数收敛性
2.
In the paper, by using the fixed point theory and differential inequality technique we study the existence and global exponential convergence of almost periodic solutions for cellular neural networks with variable delay.
利用了不动点理论和微分不等式分析等技巧,研究了变量滞细胞神经网络概周期解存在性与全局指数收敛性。
3) exponential convergence
指数收敛
1.
Moreover, the control laws using smooth time varying feedback do not stabilize the system at exponential convergence rate.
已有的光滑时变反馈方法是非指数收敛的 。
2.
Existence and exponential convergence of periodic oscillatory solution for BAM neural networks with delays is discussed by using fixed-point theorem,constructing suitable Lyapunov functions,and some analysis techniques.
应用Banach空间的不动点定理并通过构造适当的Lyapunov函数,结合一些分析的技巧研究了时滞BAM神经网络周期振荡解的存在性和指数收敛性。
3.
The feed-forward controller makes the practical robot trace in nominal system converge to the desired one with an exponential convergence rate,while the feedback controller makes the error be bounded in terminal.
基于这种线性状态方程,利用李雅普诺夫函数方法分别针对机器人标称模型和有外界不确定性干扰时,设计前馈控制器和反馈控制器,使得机器人的实际运动轨迹在标称模型下,指数收敛于所给定的期望运动轨迹;在有外界不确定性干扰时,它与期望轨迹的误差是终值有界的。
4) converge exponentially
指数收敛
1.
And it is proved that all other solutions converge exponentially to the above ω-periodic solution.
假设具有时滞的Hopfield神经网络的每个输出响应函数是满足Lipschitz条件的有界函数,当该网络的输入信号始终以正常数ω为周期,并且在网络参数满足一定的条件时,通过构造适当的Lyapunov泛函的方法,得到了该类网络必存在唯一的ω-周期解,并且其余各解都按指数收敛于该周期解的一些判据,通过实例对所得到的判据进行了直观性解释。
2.
In this paper, by constructing Liapunov functional and some analysis techniques, we study the periodic solutions of a neural network as follows: dxdt=-x(t)-α tanh+I1(t) dydt=-y(t)-α tanh+I2(t) and obtain some sufficient conditions to ensure the network exist a unique periodic solution, and its all solutions converge exponentially to the periodic solution.
本文通过构造适当的Lyapunov泛函和一些分析技巧研究如下二元神经网络dxdt=-x(t)-αtanh[y(t)-by(t-σ)]+I1(t)dydt=-y(t)-αtanh[x(t)-bx(t-τ)]+I2(t)的周期解,获得了该网络存在唯一周期解的充分条件且证明了所有其他解都指数收敛于此周期解。
5) Exponent of Convergence
收敛指数
1.
We give some estimates about the exponent of convergence of the quasiconformal Fuchsian group G =(?)Γ(?)-1.
根据H2上的双曲距离在拟共形变换下的拟不变性,给出了K-拟共形抛物循环Fuchs群的收敛指数的估计。
2.
In this paper,we investigated the zeros of meromorphic solutions of higher order linear differential equationsf~((k))+A_(k-1)f~((k-1))+…+A_0f=F where A_0(z),A_1(z),…,A_(k-1)(z),F(z)≠0 are meromorphic functions,when A_0(z) has larger growth than any other A_j(z)(j≠0),we obtain some precise estimates of the exponent of convergence of the zero-sequence of meromorphic solutions for the above equation.
如果A0(z),A1(z),…,Ak-1(z),F(z)≠0为亚纯函数,且当A0(z)比其它Aj(z)(j≠0)有较快增长级时,得到了该微分方程亚纯解的零点收敛指数的精确估计式。
3.
The hyper order, the exponent of convergence and the hyper-exponent of convergence of zeros of solutions for some types of K-order linear differential equations with entire coefficients are discussed.
研究了几类K阶整系数线性微分方程解的超级、零点收敛指数和零点超收敛指数,得到一些精确的结果。
6) convergence
[英][kən'və:dʒəns] [美][kən'vɝdʒəns]
收敛指数
1.
In this paper,we investigate the problem of the convergence of zeros of the solution of higher order linear differential equation to small order of growth function.
主要讨论了高阶齐次线性微分方程解取小函数的点的收敛指数。
2.
In this paper,we first of all investigate the problem of the convergence of zeros of the solution of non-homogeneous linear differential equation f (k) +A k-1 f (k-1) +.
首次研究了非齐次高阶线性微分方程f(k) +Ak -1f(k -1) +… +A0 (f) =F解取小函数g的点的收敛指数问题 ,得到方程解的超级、解取小函数的超级及方程系数的级三者的关系 。
补充资料：迁移效率指数、偏好指数和差别指数
迁移效率指数、偏好指数和差别指数
迁移效率指数、偏好指数和差别指数迁移效率指数是用于测定两地间人口迁移效率的指标。它是净迁移对总迁移之比。计算公式为:EIM一摇寿纂拼又‘。。上式中，}人么夕一材方}为i、]两地净迁移人数;从少+材户为i、]两地总迁移人数;El入了为迁移效率指数。 EIM的取值范围为。至100，如某一地区的值越大，反映迁移的的影响也越大。如果计算i地区与其他一切地区之间的人口迁移效率指数EIM厂，则: }艺材。一芝Mj、}EIM汀艺。+乏M，(j笋i) 迁移偏好指数是从一个地区向另一地区的实际迁移人数与期望迁移人数之比。计算公式为:____M.___材尸2行一:一二子一一不石一二，么M“ 了厂‘.厂‘、八 }二不十二六二1 、厂厂7上式中，M“为从i地迁到j地的实际迁移量;艺材。为总的人口迁移量;尸为总人口;M尸I，j为迁移偏好指数。通过计算迁移偏好指数，可以反映各地区的相对引力。 迁移差别指数是反映具有某种特征的迁移人口与非迁移人口区别的指数。例如，专业技术人员的人数所占比重，各种文化程度人数所占比重等，以便研究人才流失和其他间题。计算公式为:M‘从IMD、一翌不丝xl。。 .义V‘ N上式中，M为迁移人数;M，为具有i特征的迁移人数;N为非迁移人数;N‘为具有i特征的非迁移人数;了八了D、为迁移差别指数。
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