ID 原文 译文
48636 该方法可以在不损失参数估计精度的条件下,用远低于奈奎斯特采样定理要求的采样速率进行采样。 The method can under the condition of no loss of accuracy of parameter estimation, using is far lower than the Nyquist sampling theorem for the sampling rate of sampling.
48637 仿真实验验证了该方法有效性,并与基于分数阶傅里叶变换(fractional Fourier transform,FRFT)估计目标径向加速度方法进行了比较。 Simulation results verify the effectiveness of the method and based on fractional Fourier transform, fractional Fourier transform, the FRFT) estimated target radial acceleration methods are compared.
48638 仿真结果表明,该方法不仅所需的信号积累时长和采样速率大大降低,并且在估计精度方面也有明显的提高。 Simulation results show that the method is not only the accumulation of signal length and sampling rate is greatly reduced, and there is a marked improvements in the estimation precision.
48639 在动态群决策中属性值往往为区间语言信息,而数值决策模型难以处理,鉴于此,构建了一种动态灰色关联群决策模型。 In a dynamic group decision-making linguistic information of attribute values are interval, and the numerical model is difficult to deal with, in view of this, a dynamic grey correlation group decision-making model is constructed.
48640 首先利用区间二元语义信息的运算法则与性质,集结信息评价矩阵;针对时间权重和专家权重已知而属性权重信息完全未知的情形,设计各时间段的正、负理想方案,以与正理想方案灰色关联度偏差最小化为目标构建多目标规划模型,确定属性权重; First using interval algorithm and properties of binary semantic information, gather information evaluation matrix;Weight and expert weight is known for time and the information on attribute weights is completely unknown, design various periods of positive and negative ideal solution, with grey correlation deviation of minimized are ideal target multi-objective programming model was constructed, and to determine the attribute weights;
48641 基于各时间段各方案对正、负理想方案的区间二元语义灰色关联度,构建方案优属度的优化模型,进而获得方案优属度的表达式。 Based on the time of positive and negative ideal solution of each scheme binary semantic interval grey correlation degree, optimal solution of the optimization model was constructed, and then obtain the optimal solution expression.
48642 最后以案例验证了所提方法的有效性和可行性。 Finally a case is given to demonstrate the feasibility and effectiveness of the proposed method.
48643 结果表明,所提方法能够较为精确地处理语言信息,在一定程度上克服基于以往语言信息处理方法造成的信息扭曲和损失。 The results show that the proposed method can more accurately processing language information, to a certain extent overcome language information processing method based on the previous information distortion and damage.
48644 针对非线性系统,提出一种基于T-S模糊模型的模型参考自适应逆扰动消除控制方法。 In view of the nonlinear system, this paper puts forward a model based on t-s fuzzy model reference adaptive inverse disturbance elimination control method.
48645 所提方法根据模糊辨识理论与模型参考自适应逆控制各自的特点,将两者相结合。 Proposed method based on fuzzy identification theory and model reference adaptive inverse control characteristics, combining the two.