This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems.For each eigen-parameter the vector variable is solve...This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems.For each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less,where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector.1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues.Simultaneously,the real and complex eigenvectors can be computed very accurately.A simpler approach to the nonlinear eigenvalue problems is proposed,which implements a normalization condition for the uniqueness of the eigenvector into the eigenequation directly.The real eigenvalues can be computed by the fictitious time integration method(FTIM),which saves computational costs compared to the one-dimensional golden section search algorithm(1D GSSA).The simpler method is also combined with the Newton iterationmethod,which is convergent very fast.All the proposed methods are easily programmed to compute the eigenvalue and eigenvector with high accuracy and efficiency.展开更多
For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversio...For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversion parameters and subdivision scheme can, not only improve the inversion process efficiency, but also ensure inversion result accuracy. The gravity inversion method based on correlation searching and the golden section algorithm is an effective potential field inversion method. It can be used to invert 2D and 3D physical properties with potential data observed on flat or rough surfaces. In this paper, we introduce in detail the density inversion principles based on correlation searching and the golden section algorithm. Considering that the gold section algorithm is not globally optimized. we present a heuristic method to ensure the inversion result is globally optimized. With a series of model tests, we systematically compare and analyze the inversion result efficiency and accuracy with different parameters. Based on the model test results, we conclude the selection principles for each inversion parameter with which the inversion accuracy can be obviously improved.展开更多
During the desing of channel transect,the paper brings forward golden section method,which is 0.618 methods.In order to reduce the calculation volume of the natural depth of water h 0 and bottomˉwidth b which apply ...During the desing of channel transect,the paper brings forward golden section method,which is 0.618 methods.In order to reduce the calculation volume of the natural depth of water h 0 and bottomˉwidth b which apply trial calculation method and graphic method,and improve the calculate precision,the mathematical model has been built up,the writer combines example to explain the train of thought,the result shows that the calculation precision is high,the correctness is tested and verified by the result which is calculated by hand.It can be referred to the hydroelectric works.展开更多
自适应最稀疏时频分析(Adaptive and Sparsest Time-Frequency Analysis,ASTFA)方法是一种新的信号分解方法,该方法将信号分解问题转化为优化问题,以得到信号的最稀疏解。优化过程采用高斯-牛顿迭代算法,但高斯-牛顿迭代算法对初值依赖...自适应最稀疏时频分析(Adaptive and Sparsest Time-Frequency Analysis,ASTFA)方法是一种新的信号分解方法,该方法将信号分解问题转化为优化问题,以得到信号的最稀疏解。优化过程采用高斯-牛顿迭代算法,但高斯-牛顿迭代算法对初值依赖性高,采用黄金分割法(Golden Section,GS)对ASTFA方法进行初值搜索,提出了基于黄金分割搜索初值的ASTFA方法(GS-ASTFA),仿真信号的分析结果验证了改进方法的有效性。继而采用该方法提取了滚动轴承故障特征值,并成功地进行了故障特征值趋势分析和寿命预测。展开更多
基金the National Science and Tech-nology Council,Taiwan for their financial support(Grant Number NSTC 111-2221-E-019-048).
文摘This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue problems.For each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less,where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector.1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues.Simultaneously,the real and complex eigenvectors can be computed very accurately.A simpler approach to the nonlinear eigenvalue problems is proposed,which implements a normalization condition for the uniqueness of the eigenvector into the eigenequation directly.The real eigenvalues can be computed by the fictitious time integration method(FTIM),which saves computational costs compared to the one-dimensional golden section search algorithm(1D GSSA).The simpler method is also combined with the Newton iterationmethod,which is convergent very fast.All the proposed methods are easily programmed to compute the eigenvalue and eigenvector with high accuracy and efficiency.
基金supported by Specialized Research Fund for the Doctoral Program of Higher Education of China(20110022120004)the Fundamental Research Funds for the Central Universities
文摘For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversion parameters and subdivision scheme can, not only improve the inversion process efficiency, but also ensure inversion result accuracy. The gravity inversion method based on correlation searching and the golden section algorithm is an effective potential field inversion method. It can be used to invert 2D and 3D physical properties with potential data observed on flat or rough surfaces. In this paper, we introduce in detail the density inversion principles based on correlation searching and the golden section algorithm. Considering that the gold section algorithm is not globally optimized. we present a heuristic method to ensure the inversion result is globally optimized. With a series of model tests, we systematically compare and analyze the inversion result efficiency and accuracy with different parameters. Based on the model test results, we conclude the selection principles for each inversion parameter with which the inversion accuracy can be obviously improved.
文摘During the desing of channel transect,the paper brings forward golden section method,which is 0.618 methods.In order to reduce the calculation volume of the natural depth of water h 0 and bottomˉwidth b which apply trial calculation method and graphic method,and improve the calculate precision,the mathematical model has been built up,the writer combines example to explain the train of thought,the result shows that the calculation precision is high,the correctness is tested and verified by the result which is calculated by hand.It can be referred to the hydroelectric works.
