ID	原文	译文
8534	相比传统RVM,所提方法首先在预测模型训练之前通过计算各类基函数的后验概率来选取最适合训练样本结构特点的基函数。	Compared with the traditional RVM, the proposed method first before forecasting model training through the calculation of posterior probability of all kinds of basis function to select the most suitable for the training sample structure characteristic basis function.
8535	然后在训练中采用优化的增量学习流程来实现各核参数的快速自适应选取。	And then optimize the incremental learning in training process to realize the rapid and adaptive selection of the nuclear parameters.
8536	最后通过对电子系统状态参量的相空间重构,从而将AM-RVM应用到电子系统的状态预测中。	Finally through to the electronic system state parameters of phase space reconstruction, thus the applications of AM - RVM to electronic system state prediction.
8537	混沌时间序列预测及雷达发射机高压电源状态预测实验的结果表明,所提方法在预测精度与训练效率上优于传统RVM。	Chaotic time series prediction and radar transmitter high voltage power supply state prediction experiment results show that the proposed method superior to the traditional RVM in prediction accuracy and training efficiency.
8538	为了同时利用证据焦元的基本概率赋值和焦元的基数信息解决DS(Dempster-Shafer,DS)证据理论高冲突问题,并考虑数据融合的抗噪声和干扰能力,提出采用基于焦元信息能量的先验信息比值演变函数对证据源和组合规则进行修正的算法。	To at the same time using the basic probability assignment and evidence of jiao yuan jiao yuan base information to solve the DS (Dempster - Shafer, DS) evidence theory with high conflict problem, and consider the ability to resist noise and interference of data fusion, is proposed based on jiao yuan information energy ratio of priori information evolution function for the source and evidence combination rule modification algorithm.
8539	为了进一步降低算法计算量,利用多元素焦元信任值向单元素焦元分配以及决策集约简方法,进一步优化算法性能,提高算法大数据量适应能力。	Algorithm in order to further reduce the amount of calculation, the use of multielement jiao yuan jiao yuan trust value to the single element distribution as well as the method of decision-making and intensive Jane, further optimization algorithm performance, large amount of data to improve algorithm adaptability.
8540	实验结果验证了优化算法的正确性和有效性。	The experimental results verify the correctness and effectiveness of the optimization algorithm.
8541	基于宽带逆合成孔径雷达原理,提出一种动态产生微动目标有源欺骗式干扰信号的合成方法。	Based on the principle of broadband inverse synthetic aperture radar, this paper puts forward a dynamic producing micro synthesis methods of target active deception jamming signal.
8542	在多散射中心假目标模板中引入了目标全姿态运动模型、全极化散射模型,推导了与进动参数直接相关的微多普勒及姿态角表达式;	In the center of the multiple scattering of false target templates introduced full attitude motion model, full polarization scattering model, and the precession parameters was deduced directly related to the micro-doppler and attitude Angle expressions;
8543	建立了目标本地极化基到任意雷达极化基下的散射矩阵变换关系;	Established the goal of local polarization base to any radar polarization scattering matrix transformation relation in the base;