Mathematics and computer sciences need suitable methods for numerical calculations of integrals. Classical methods, based on polynomial interpolation, have many weak sides: they are useless to interpolate the function...Mathematics and computer sciences need suitable methods for numerical calculations of integrals. Classical methods, based on polynomial interpolation, have many weak sides: they are useless to interpolate the function that fails to be differentiable at one point or differs from the shape of polynomials considerably. We cannot forget about the Runge’s phenomenon. To deal with numerical interpolation and integration dedicated methods should be constructed. One of them, called by author the method of Hurwitz-Radon Matrices (MHR), can be used in reconstruction and interpolation of curves in the plane. This novel method is based on a family of Hurwitz-Radon (HR) matrices. The matrices are skew-symmetric and possess columns composed of orthogonal vectors. The operator of Hurwitz-Radon (OHR), built from that matrices, is described. It is shown how to create the orthogonal and discrete OHR and how to use it in a process of function interpolation and numerical integration. Created from the family of N-1 HR matrices and completed with the identical matrix, system of matrices is orthogonal only for vector spaces of dimensions N = 2, 4 or 8. Orthogonality of columns and rows is very significant for stability and high precision of calculations. MHR method is interpolating the curve point by point without using any formula of function. Main features of MHR method are: accuracy of curve reconstruction depending on number of nodes and method of choosing nodes;interpolation of L points of the curve is connected with the computational cost of rank O(L);MHR interpolation is not a linear interpolation.展开更多
提出了一种基于Radon-Ambiguity变换(Radon-Ambiguity Transform,RAT)的线性调频(Linear Frequency Modulated,LFM)信号时/频差快速联合估计的算法.根据LFM信号在多个不同角度上的RAT峰值位置建立一组以信号间时差和频差为未知量的方程...提出了一种基于Radon-Ambiguity变换(Radon-Ambiguity Transform,RAT)的线性调频(Linear Frequency Modulated,LFM)信号时/频差快速联合估计的算法.根据LFM信号在多个不同角度上的RAT峰值位置建立一组以信号间时差和频差为未知量的方程组,求解方程组即可得到时/频差的估计值.对于存在噪声的信号,RAT误差会导致方程组不能直接求解,为了抑制噪声干扰,采用最小二乘法估计时/频差.本文算法无需计算二维平面上各点的模糊函数值,并且由于离散RAT可以通过快速傅里叶变换快速实现,具有所需运算量低的优点.仿真实验表明,相比于常见的基于模糊函数峰值搜索的时/频差估计算法,本文算法在保证时/频差估计精度的同时能够显著提高运算效率.展开更多
文摘Mathematics and computer sciences need suitable methods for numerical calculations of integrals. Classical methods, based on polynomial interpolation, have many weak sides: they are useless to interpolate the function that fails to be differentiable at one point or differs from the shape of polynomials considerably. We cannot forget about the Runge’s phenomenon. To deal with numerical interpolation and integration dedicated methods should be constructed. One of them, called by author the method of Hurwitz-Radon Matrices (MHR), can be used in reconstruction and interpolation of curves in the plane. This novel method is based on a family of Hurwitz-Radon (HR) matrices. The matrices are skew-symmetric and possess columns composed of orthogonal vectors. The operator of Hurwitz-Radon (OHR), built from that matrices, is described. It is shown how to create the orthogonal and discrete OHR and how to use it in a process of function interpolation and numerical integration. Created from the family of N-1 HR matrices and completed with the identical matrix, system of matrices is orthogonal only for vector spaces of dimensions N = 2, 4 or 8. Orthogonality of columns and rows is very significant for stability and high precision of calculations. MHR method is interpolating the curve point by point without using any formula of function. Main features of MHR method are: accuracy of curve reconstruction depending on number of nodes and method of choosing nodes;interpolation of L points of the curve is connected with the computational cost of rank O(L);MHR interpolation is not a linear interpolation.
文摘提出了一种基于Radon-Ambiguity变换(Radon-Ambiguity Transform,RAT)的线性调频(Linear Frequency Modulated,LFM)信号时/频差快速联合估计的算法.根据LFM信号在多个不同角度上的RAT峰值位置建立一组以信号间时差和频差为未知量的方程组,求解方程组即可得到时/频差的估计值.对于存在噪声的信号,RAT误差会导致方程组不能直接求解,为了抑制噪声干扰,采用最小二乘法估计时/频差.本文算法无需计算二维平面上各点的模糊函数值,并且由于离散RAT可以通过快速傅里叶变换快速实现,具有所需运算量低的优点.仿真实验表明,相比于常见的基于模糊函数峰值搜索的时/频差估计算法,本文算法在保证时/频差估计精度的同时能够显著提高运算效率.
