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- Pseudo - chaotic Time Hopping(PCTH) 伪混沌跳时序列
- A New Multi - modulation Method of UWB: Pseudo - chaotic Coding and Time Hopping 一种新的超宽带多用户调制方式:伪混沌编码跳时调制
- Simulations show these two methods are effective for chaotic time series prediction,including ... 仿真表明,两种模型均能有效预报舰船摇荡极短期运动。
- Still, those who study Psychoportation try the impossible, and in some cases succeed with powers such as time hop and time regression. 然而，学习心灵传送系的人尝试打破这种不可能，并且某些情况下成功了，例如“时间跳跃”和“时光倒流”异能。
- On the basis of chaotic time series,this paper uses the BP neural network method to forecast the power load,and analyzes the model characteristic. 在混沌时间序列的基础上,应用BP神经网络对电力负荷进行了预测,并对模型特性进行了分析。
- As a new type of recurrent neural network,echo state network(ESN) is applied to nonlinear system identification and chaotic time series prediction. ESN(回声状态网络)是一种新型的递归神经网络;可有效处理非线性系统辨识以及混沌时间序列预测问题.
- Simulations show that RBF networks models have good fitness and high accuracy of single and multistep prediction to the chaotic time series. 仿真结果表明,RBF网络模型对混沌时间序列有比较强的拟合能力和比较高的一步及多步预测精度。
- Guo S B,Xiao X C.Determining rank of Volterra adaptive filter of chaotic time series [J].Journal of Electronics and Information Technology,2002,24(10):1334-1340. [13]郭双冰;肖先赐.;混沌时间序列的Volterra自适应预测滤波器定阶[J]
- Zhang J S,Xiao X C.A reduced parameter second-order volterra filter with application to nonlinear adaptive prediction of chaotic time series [J].Acta Phys Sin,2001,50(7):1249. [4]张家树;肖先赐.;用于混沌时间序列自适应预测的一种少参数二阶Volterra滤波器[J]
- In the case of chaotic time series, using phase space reconstruction and probability raising method can extract the UPO’s embedded in the chaotic time series. 混沌时间序列的情况下，通过相空间重构技术和概率提升法可以计算嵌入于其中的不稳定周期轨道。
- time hopping - pulse position modulation TH-PPM
- The new method treats the problem of parameter estimation and noise reduction for chaotic time series as a nonlinear minimization process and solves it using steepest descent algorithm. 这种新方法把对混沌时间序列的参数估计和噪声抑制看作是一种最小化过程，并利用了最速梯度下降方法解决。
- time hopping pulse position modulation 跳时脉冲位置调制
- In addition,GPM integrates the results from Nonlinear Time Series Analysis (NTSA) to adjust the parameters and as the criterion of founded models. The simulation shows the effectiveness of such improvements on modeling chaotic time series. 此外;演化建模的实现结合了非线性时间序列分析(NTSA)的结果;以NTSA的结果指导演化建模参数的选取并作为模型优劣的评判标准;改进了经典GP算法对混沌系统建模的应用效果.
- time hopping pulse position modulation(TH-PPM) 跳时脉位调制
- Based on the analysis of polynomial nonlinear adaptive prediction methods existed already, a DCT domain quadratic predictor for real-time prediction of low-dimension chaotic time series is proposed. 在分析现有多项式非线性自适应预测法的基础上，提出了混沌时间序列预测的DCT域二次实时自适应滤波预测法；
- Frequency Time Hopping Multiple Access 频率时间跳跃多址
- Because the existing methods are sensitive to noise in identifying chaotic attractor,it is very important to research the method of identifying chaotic time series which is corrupted by noise. 由于现有的混沌吸引子识别方法对噪声敏感,研究带噪声的时间序列的混沌识别方法就显得特别重要。
- The new method treated the problem of parameter estimation and filtering for chaotic time series as a nonlinear minimisation process and solved it by using a steepest descent algorithm. 这种新方法把对混沌时间序列的参数估计和滤波看作是一种最小化过程，并利用了最速梯度下降方法解决。
- Miss Spider: Harvest Time Hop and Fly (U) 蜘蛛小姐:收[打印本页]
