该文提出了一种基于魏格纳分布(Wigner-Ville Distributed,WVD)和重构时间采样(Reconstruction time sample,RTS)的空中机动目标检测和参数估计方法。该方法首先利用雷达回波的空域采样来重构时域采样,相当于增加了单个阵元的脉冲采样点...该文提出了一种基于魏格纳分布(Wigner-Ville Distributed,WVD)和重构时间采样(Reconstruction time sample,RTS)的空中机动目标检测和参数估计方法。该方法首先利用雷达回波的空域采样来重构时域采样,相当于增加了单个阵元的脉冲采样点数,然后再对重构后的数据进行WVD变换来估计目标的参数。该方法能够在方位信息未知,脉冲数较少的情况下有效地实现对机动目标的检测与参数估计。仿真结果验证了该方法的有效性。展开更多
The C-C method was adopted to analyze the nonlinear characteristics of masseter electromyography （EMG） signals and the chaotic degree by the largest Lyapunov exponent （LLE） of different genders and sides. First, t...The C-C method was adopted to analyze the nonlinear characteristics of masseter electromyography （EMG） signals and the chaotic degree by the largest Lyapunov exponent （LLE） of different genders and sides. First, the embedding dimension and the delay time were obtained through this method, then the phase space was reconstructed to resume the chaotie attractor and determine the LLE. The result shows that the trajectory of attractor is denser than Chen＇s attractor, and the LLE is positive, which means that not only the signal has the character of chaos, but also the chaotic degree of masseter EMG is relatively high. According to the value of the LLE, the chaotic degree of men＇s masseter EMG is higher than that of women＇s; when the dentition is normal, the chaotic degree of two sides is almost the same. Then, a conclusion can be deduced that if the LLE of both sides are in great difference, the unilateral mastication is likely to exist, which means that the nonlinear characteristics of masseter EMG can be applied to predict the unilateral mastication.展开更多
According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are comput...According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.展开更多
文摘该文提出了一种基于魏格纳分布(Wigner-Ville Distributed,WVD)和重构时间采样(Reconstruction time sample,RTS)的空中机动目标检测和参数估计方法。该方法首先利用雷达回波的空域采样来重构时域采样,相当于增加了单个阵元的脉冲采样点数,然后再对重构后的数据进行WVD变换来估计目标的参数。该方法能够在方位信息未知,脉冲数较少的情况下有效地实现对机动目标的检测与参数估计。仿真结果验证了该方法的有效性。
文摘The C-C method was adopted to analyze the nonlinear characteristics of masseter electromyography （EMG） signals and the chaotic degree by the largest Lyapunov exponent （LLE） of different genders and sides. First, the embedding dimension and the delay time were obtained through this method, then the phase space was reconstructed to resume the chaotie attractor and determine the LLE. The result shows that the trajectory of attractor is denser than Chen＇s attractor, and the LLE is positive, which means that not only the signal has the character of chaos, but also the chaotic degree of masseter EMG is relatively high. According to the value of the LLE, the chaotic degree of men＇s masseter EMG is higher than that of women＇s; when the dentition is normal, the chaotic degree of two sides is almost the same. Then, a conclusion can be deduced that if the LLE of both sides are in great difference, the unilateral mastication is likely to exist, which means that the nonlinear characteristics of masseter EMG can be applied to predict the unilateral mastication.
基金Project(70671039) supported by the National Natural Science Foundation of China
文摘According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.
