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Because of the associative law for addition, we can define multiplication based on addition, a b means a+a+…+a,adding a with b times.

正是由于加法的结合使得我们可以在加法的基础上定义乘法,就是重复加法的简便运算:a b=a+a+…+a,对a重复相加b次。

Similarly, the addition of any three natural numbers must satisfy associative law:+c=a+, and then we can verify that for any n natural numbers, the results of adding is the same in any associative way which keep the order of numbers.

类似地任何三个自然数可以有结合:+c=a+,进而可以证明任何n个数的任何结合方式进行加法所得的结果是一致的。

Table 2.1 at the end of this chapter summarizes precedence and associativity for all operators.

本章末尾的表2-1完整总结了所有运算符的优先级和结合

The ten I will give you because he has forsaken me and has worshiped Astarte, goddess of the Sidonians, Chemosh, god of Moab, and Milcom, god of the Ammonites; he has not followed my ways or done what is pleasing to me according to my statutes and my decrees, as his father David did.

因为他背弃了我,崇拜了漆冬人的女神阿市托勒特、摩阿布人的神革摩士和阿孟人的神米耳公。他没有像他父亲达味那样履行我的道路,行我视为正义的事,恪守我的例和诫命。

In 1981,Ehm sloved the existence and the smoothness properties and the asymptotic behavior of the local time.

中文摘要: Ehm在1981年解决了多指标稳定过程局部时的存在性、连续性及其Hlder;Xiao在2003年讨论了可加Lévy过程局部时的相应的问题。

The overall control scheme and the weight update laws based on Lyapunov stability theory can guarantee the system stability and asymptotic convergence of the tracking error to zero, and attenuate the effect of the disturbance on system to a prescribed level.

总体控制方案及基于李亚普诺夫稳定性理论的权值更新保证了系统的稳定性及跟踪误差渐近收敛于零,并使干扰对系统的影响衰减到指定的性能指标。

When the errors meet certain requirements, the adaptive law based on the Lyapunov stability further adjusts the weights of networks to ensure the asymptotic convergence of the tracking error to be zero.

当误差满足一定要求时,根据Lyapunov稳定性理论的自适应进一步调整网络权值,以保证机械手位置误差和速度跟踪误差渐近收敛于零。

By introducing a differential-difference adaptive law, an adaptive repetitive learning control strategy is designed to ensure the asymptotic convergence of the extended tracking error in the sense of square error norm.

通过引进微分-差分参数自适应,设计了一种自适应控制策略,使广义跟踪误差在误差平方范数意义下渐近收敛于零。

A differential difference type adaptive law and an adaptive iterative learning controller are constructed to ensure the asymptotic convergence of tracking errors in the sense of square error norm on the finite interval, by introducing a Lyapunov-like function, a sufficient condition of the convergence of the method is given.

通过引入微分-差分自适应学习,设计了一种自适应控制策略,使得跟踪误差在一个有限区间上的积分渐近收敛于零;通过构造Lyapunov-like函数,给出了闭环系统收敛的一个充分条件。

A differential-difference mixed-type adaptive law and an adaptive learning control method are constructed to ensure the asymptotic convergence of the extended tracking error in the sense of square error norm.

通过引进新颖的微分-差分混合型参数自适应,使广义跟踪误差在误差平方范数意义下渐近收敛于零。

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