Next, the thesis analysis the characterization of Roundtrip time delay (RTT). The RTT time series collected from the Internet are studied statistically by using both linear and nonlinear methods.
其次，对网络时延(RTT)特性进行了分析，利用线性和非线性方法对从互联网上采集的RTT时间序列进行统计分析。
The delay-coordinate method is adopted to reconstructed the space phase, and to analyze the single time series in the non-linear systems and resume the nonlinear kinetics characteristics.
采用延迟坐标状态空间这种相空间重构方法，对非线性系统中的单一时间序列进行分析，从中恢复出系统内部存在的非线性动力学特性。
A new multi-branch time delay neural network is adopted to conduct prediction research on chaotic time series.
采用新型多重分支时间延迟神经网络进行混沌时间序列预测研究。
Based on the delay-coordinate reconstruction and bilinear expressions in the phase space of a chaotic system, a bilinear adaptive filter was designed to predict low-dimensional chaotic time series.
基于混沌动力系统相空间的延迟坐标重构和双线性表达式，设计了预测混沌时间序列的双线性自适应预测滤波器。
By introducing a sensitivity parameter, the original optimal output tracking control problem is transformed into a series of two-point boundary value problems without time-advance or time-delay terms.
通过引入一个灵敏度参数，将原最优输出跟踪控制问题转化为不含超前项和时滞项的一族两点边值问题。
By phase space reconstruction, choosing the most suitable delay time and embedding dimension in order to embed time series which reflect the demanding into the phase space.
通过相空间重构技术，选取合适的延迟时间和嵌入维数，将反映市场需求的时间序列嵌入到相空间中。
A routing algorithm based on time series prediction for delay tolerant network is proposed.
本文提出了一种基于时间序列预测的延迟容忍网络路由算法。
Time delay method was used to reconstruct the phase space of underwater noise time series based on nonlinear dynamics theory.
以非线性动力学理论中的相空间重构理论为基础，利用延时法对水下噪声时间序列信号进行了相空间重构。
First, one dimensional time series are embedded into a high dimensional phase space according to time-delay theory.
首先用时间延迟方法将一维时间序列重构到高维相空间。
Based on the prediction method of univariate time series, and according to the proper selection of dimension and delay time, the time series can be predicted precisely.
根据单变量时间序列的混沌预测方法，只要嵌入维数和延迟时间选择得合理，便能进行精确的预测。
Based on the prediction method of univariate time series, and according to the proper selection of dimension and delay time, the time series can be predicted precisely.
根据单变量时间序列的混沌预测方法，只要嵌入维数和延迟时间选择得合理，便能进行精确的预测。
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