ID 原文 译文
49116 利用退化模型的低通滤波器的双正交滤波器得到一个空域双正交映射,放大图像完全满足退化模型,使放大图像对于退化模型可逆。 Degradation model of low pass filter of biorthogonal filter get an airspace biorthogonal mapping, enlarge the image completely meet the degradation model, make the magnified image for reversible degradation model.
49117 仿真实验表明,与其他算法相比,所提算法有较好的性能,得到的放大图像更加自然,在弱边缘和中等强度边缘都有更好的视觉效果。 Simulation experiments show that compared with other algorithms, the proposed algorithm has good performance, get a larger version of the image is more natural, on the edge of the weak edges and moderate intensity has better visual effect.
49118 为解决折叠翼飞行器初段飞行中气动特性变化大且易受环境扰动影响、控制鲁棒性要求高的问题,将飞行器物理模型的实时辨识与非线性动态逆方法相结合,设计可重构飞行控制器。 To solve the problem in the folding wing aircraft flying 53-46 aerodynamic characteristics change large and vulnerable to environmental disturbance, control the problem of high robustness requirement, the physical model of real-time identification and nonlinear dynamic inversion method, combining design reconfigurable flight controller.
49119 基于迭代扩展卡尔曼滤波与渐消记忆最小二乘,将气动特性辨识一步方法分解为状态量和参数值的两步辨识,算法更易于在线实现。 Extended kalman filtering based on iterative least squares with fading memory, the method of aerodynamic characteristics identification step into state variable and parameter values of the two step identification, more easier to implement online algorithm.
49120 通过实时辨识更新动态逆控制器参考模型,消除模型逆误差,实现可重构控制。 Updated by real-time identification reference model, the dynamic inversion controller to eliminate model inversion error, to realize reconfigurable control.
49121 针对某型折叠翼飞行器的6自由度仿真结果表明,在飞行器自身气动特性大幅变化且考虑外界未知扰动情况下,控制器满足设计要求,具有较强的鲁棒性。 Six degrees of freedom against certain type folding wing aircraft simulation results show that the aerodynamic characteristics of the aircraft itself significantly change and the unknown external disturbance, is considered the controller meet the design requirements, and has strong robustness.
49122 为了验证平均秩次法在估计完全删失数据分布函数参数时的有效性,设计了一种明晰平均秩次法适用范围的蒙特卡罗仿真方法。 In order to verify the average rank method in estimating completely delete the validity of the data distribution function parameter, we design a clear scope of average rank method monte carlo simulation method.
49123 该方法考虑现场故障数据的实际生成过程,以机群为研究对象,通过飞机架数、飞行天数、日利用率动态变化驱动故障样本、删失比变化,获取故障间隔时间的完全删失数据。 The method considering the field failure data of actual generation process, fleet as the research object, through the utilization rate of the plane frame number, flight number, date dynamic drive fault samples, delete than change, obtain the time between failures completely delete data loss.
49124 结合拉依达准则,确定了平均秩次法的计算错误率。 Combined with pull up to standards, to determine the average rank method calculation error rate.
49125 仿真结果表明,样本量在9.1,删失比为0.328时,错误率达到28.9%,此条件下,平均秩次法已经不适用。 The simulation results show that the sample size in 9.1, delete loss of ratio 0.328, the error rate of 28.9%, under this condition, the average rank method is not applicable.