In this paper. we give a decomposition depending on p(1≤p≤n-2) orthonormaldirections assigned for nonsingular linear transformation F on a n-dimension (n≥3)Euclidean space En, and then prove foal there exist q(q=n-...In this paper. we give a decomposition depending on p(1≤p≤n-2) orthonormaldirections assigned for nonsingular linear transformation F on a n-dimension (n≥3)Euclidean space En, and then prove foal there exist q(q=n-p) quasi-Principaldirections.for F depending on the preceding p orthonormal directions. As applicance ofthe preceding result, we derive that there exist at least two orthonormal principaldirections of strain in arbitrary plane of body which is in homogeneous deformation,and strain energy density is.function of 5 real numbers under arbitrary quasi-principalbase.for the preceding nonsingular linear transformation.展开更多
针对稀疏线阵波达方向估计精度较低问题,提出一种稀疏线阵双迭代傅里叶优化方法。基于阵列孔径原理,利用阵列因子与阵元激励间的傅里叶变换关系,构建稀疏线阵构型优化目标函数;提出双迭代傅里叶变换算法,制定合理的旁瓣阈值和旁瓣约束条...针对稀疏线阵波达方向估计精度较低问题,提出一种稀疏线阵双迭代傅里叶优化方法。基于阵列孔径原理,利用阵列因子与阵元激励间的傅里叶变换关系,构建稀疏线阵构型优化目标函数;提出双迭代傅里叶变换算法,制定合理的旁瓣阈值和旁瓣约束条件,依据稀疏率和阵元数将孔径自适应分区,以阵列峰值旁瓣和孔径为约束,由双层嵌套循环迭代优化阵列麦克风数量和位置,获得更低的阵列峰值旁瓣电平。数值仿真和实验结果表明,根据该方法获得的49.5λ孔径、23%稀疏率的稀疏阵列峰值旁瓣电平为-21.59 dB,主瓣宽度为1.03°,角度分辨率为1°,估计误差小于0.01。与其他方法对比,峰值旁瓣低1 d B,优化效率提升50%,由此可证明该方法的有效性和快速性。展开更多
针对摄像机位姿问题提出了一种加权线性方法,其关键思想是通过加权使经典线性方法的代数误差近似于重投影算法的几何误差,从而达到接近于最大似然估计(Levenberg-Marquardt简称ML)的精度.通过对经典DLT(direct linear transformation)...针对摄像机位姿问题提出了一种加权线性方法,其关键思想是通过加权使经典线性方法的代数误差近似于重投影算法的几何误差,从而达到接近于最大似然估计(Levenberg-Marquardt简称ML)的精度.通过对经典DLT(direct linear transformation)算法和EPnP算法使用加权的方法,给出了加权DLT算法(WDLT)和加权EPnP算法(WEPnP).大量模拟数据和真实图像实验结果均表明,WDLT和WEPnP算法不仅能提高DLT和EPnP算法的精度,而且在深度较小的情况下优于Lu的非线性算法.展开更多
文摘In this paper. we give a decomposition depending on p(1≤p≤n-2) orthonormaldirections assigned for nonsingular linear transformation F on a n-dimension (n≥3)Euclidean space En, and then prove foal there exist q(q=n-p) quasi-Principaldirections.for F depending on the preceding p orthonormal directions. As applicance ofthe preceding result, we derive that there exist at least two orthonormal principaldirections of strain in arbitrary plane of body which is in homogeneous deformation,and strain energy density is.function of 5 real numbers under arbitrary quasi-principalbase.for the preceding nonsingular linear transformation.
文摘针对稀疏线阵波达方向估计精度较低问题,提出一种稀疏线阵双迭代傅里叶优化方法。基于阵列孔径原理,利用阵列因子与阵元激励间的傅里叶变换关系,构建稀疏线阵构型优化目标函数;提出双迭代傅里叶变换算法,制定合理的旁瓣阈值和旁瓣约束条件,依据稀疏率和阵元数将孔径自适应分区,以阵列峰值旁瓣和孔径为约束,由双层嵌套循环迭代优化阵列麦克风数量和位置,获得更低的阵列峰值旁瓣电平。数值仿真和实验结果表明,根据该方法获得的49.5λ孔径、23%稀疏率的稀疏阵列峰值旁瓣电平为-21.59 dB,主瓣宽度为1.03°,角度分辨率为1°,估计误差小于0.01。与其他方法对比,峰值旁瓣低1 d B,优化效率提升50%,由此可证明该方法的有效性和快速性。
文摘针对摄像机位姿问题提出了一种加权线性方法,其关键思想是通过加权使经典线性方法的代数误差近似于重投影算法的几何误差,从而达到接近于最大似然估计(Levenberg-Marquardt简称ML)的精度.通过对经典DLT(direct linear transformation)算法和EPnP算法使用加权的方法,给出了加权DLT算法(WDLT)和加权EPnP算法(WEPnP).大量模拟数据和真实图像实验结果均表明,WDLT和WEPnP算法不仅能提高DLT和EPnP算法的精度,而且在深度较小的情况下优于Lu的非线性算法.