通过概率密度函灵数及平均相轨线的分析，指出该系统在这两种情况下作所谓的混沌随机运动。
Through the analysis of their probability density function and mean trajectory, it shows that this system in these two cases can occur chaotic stochastic motion.
混沌是指发生在确定性系统中貌似随机的无规则或不规则运动。
Chaos is a kind of seemingly random, chance or irregular movement, which appears in a definiteness system.
混沌是发生在确定性非线性动力学系统中的一种内在随机运动。
Chaos is an inner stochastic motion happening in fixed non-linear dynamics system.
变尺度混沌优化（MSCOA）是一种改进的混沌优化方法（COA），利用混沌运动的内在随机性、遍历性和规律性进行全局寻优；
Mutative scale chaos optimization algorithm (MSCOA) is a modified chaos optimization algorithm (COA), which possesses the properties of randomness, ergodicity and regularity of chaos movement.
混沌是非线性确定性系统中由于内在随机性而产生的外在复杂表现，是一种貌似随机的非随机运动。
Chaos is an outer complex behavior of nonlinear definite system, produced by the system's internal stochastic property, a non-stochastic movement while looks like stochastic.
用相空间表示点的运动来描写混沌态的赝随机变化。
The pseudo random of chaotic state is described according to the motion of point in phase.
系统做混沌运动，测度同步时系统的相位移是随机行走的，没有测度同步点与相锁定点的重合。
When the coupled systems are chaotic, that is, the largest Lyapunov exponent is positive, the measure synchronization does not go with the phase synchronization, the phase locking changes random walk.
混沌是一种确定性的非线性运动，它不是随机的但对初始条件敏感依赖，许多领域的研究证实了混沌的存在。
Chaos is a deterministic nonlinear structure, which is not a stochastic process, but sensitive dependence on initial conditions. Studies in numerous fields have shown the existence of chaos dynamics.
混沌是非线性确定系统中由于内禀随机性而产生的外在复杂表现，是一种貌似随机的运动。
Chaos is a exterior and complex behavior because of inner random in nonlinear definitive system, and a movement seemingly similar to random.
但是混沌系统是由非线性动力机制决定的确定性系统，貌似随机运动的混沌系统内部存在确定性规律，所以混沌时间序列是短期可预测的。
But chaos is a deterministic system determined by the nonlinear dynamical mechanism. There is a deterministic rule in the interior of the chaotic system which is seemed as a random move.
分析了已有的序列线性复杂度分析方法，提出了用近似熵算法计算混沌运动的测度熵，作为衡量混沌伪随机序列复杂度的标准。
In this paper, the conventional pseudo-random sequence linear complexity is discussed, and a new criterion is proposed, based on the approximate entropy.
分析了已有的序列线性复杂度分析方法，提出了用近似熵算法计算混沌运动的测度熵，作为衡量混沌伪随机序列复杂度的标准。
In this paper, the conventional pseudo-random sequence linear complexity is discussed, and a new criterion is proposed, based on the approximate entropy.
应用推荐