通过将混沌伪随机序列看成一个符号序列，提出了用符号动力学的方法来分析混沌伪随机序列的复杂度。
By considering a chaotic pseudo_random sequence as a symbolic sequence, we present a symbolic dynamics approach for the complexity analysis of chaotic pseudo_random sequences.
介绍了机械臂动力学模型并进行了线性化处理，以降低算法复杂度、保证实时性。
The dynamic model of manipulators is introduced and its linearization is conducted to reduce algorithm complexity and guarantee real-time.
利用这一模型，可以为不同复杂度的航天动力学建模提供支持，方便构筑面向具体问题的应用。
The models can provide support on various complexity simulation and the application question-oriented can be built expediently.
结果发现细粒化复杂度比粗粒化复杂度描述动力学更加精确。
Result it was found that the fine graining complexity measure is more precise in describing the dynamics than the coarse graining complexity measure.
结果发现细粒化复杂度比粗粒化复杂度描述动力学更加精确。
Result it was found that the fine graining complexity measure is more precise in describing the dynamics than the coarse graining complexity measure.
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