Due to the diversity of work requirements and environment,the number of degrees of freedom(DOFs)and the complexity of structure of industrial robots are constantly increasing.It is difficult to establish the accurate ...Due to the diversity of work requirements and environment,the number of degrees of freedom(DOFs)and the complexity of structure of industrial robots are constantly increasing.It is difficult to establish the accurate dynamical model of industrial robots,which greatly hinders the realization of a stable,fast and accurate trajectory tracking control.Therefore,the general expression of the constraint relation in the explicit dynamic equation of the multi-DOF industrial robot is derived on the basis of solving the Jacobian matrix and Hessian matrix by using the kinematic influence coefficients method.Moreover,an explicit dynamic equation with general constraint relation expression is established based on the Udwadia-Kalaba theory.The problem of increasing the time of establishing constraint relationship when the multi-DOF industrial robots complete complex task constraints is solved.With the SCARA robot as the research object,the simulation results show that the proposed method can provide a new idea for industrial robot system modeling with complex constraints.展开更多
This paper establishes the relation between APLs and direct input coefficients through Sherman-Morrison formulation.On such a basis,elasticity matrix can be calculated for each element of the APLs matrix,which measure...This paper establishes the relation between APLs and direct input coefficients through Sherman-Morrison formulation.On such a basis,elasticity matrix can be calculated for each element of the APLs matrix,which measures the percentage change in the APLs-matrix element brought by one percentage change in every direct input coefficient.Hence,the percentage change in each APLs-matrix element caused by the real percentage change in each coefficient with other coefficients fixed can be drawn,from which it is easily to find out the APLs-important coefficients and is useful to explain the reason for change in the matrix.The empirical application studies the Chinese economy.What's more,the method is applied under different level of aggregation.The comparison between the APLs matrix of 1997 and 2002 allows the authors to visualize the elements that change dramatically.Then the methodology above is applied to explain the change from the perspective of direct input coefficients and find out the important coefficients to the Chinese APLs matrix.展开更多
The concepts of local correlation coefficient, local canonical correlation coefficients and local canonical variables of groups of random variables are defined, which generalize the classical concepts in two groups of...The concepts of local correlation coefficient, local canonical correlation coefficients and local canonical variables of groups of random variables are defined, which generalize the classical concepts in two groups of random variables.These concepts together with total corresponding concepts clarify the correlativity among groups of random variables.展开更多
In many applications, such as in multivariate meta-analysis or in the construction of multivariate models from summary statistics, the covariance of regression coefficients needs to be calculated without having access...In many applications, such as in multivariate meta-analysis or in the construction of multivariate models from summary statistics, the covariance of regression coefficients needs to be calculated without having access to individual patients’ data. In this work, we derive an alternative analytic expression for the covariance matrix of the regression coefficients in a multiple linear regression model. In contrast to the well-known expressions which make use of the cross-product matrix and hence require access to individual data, we express the covariance matrix of the regression coefficients directly in terms of covariance matrix of the explanatory variables. In particular, we show that the covariance matrix of the regression coefficients can be calculated using the matrix of the partial correlation coefficients of the explanatory variables, which in turn can be calculated easily from the correlation matrix of the explanatory variables. This is very important since the covariance matrix of the explanatory variables can be easily obtained or imputed using data from the literature, without requiring access to individual data. Two important applications of the method are discussed, namely the multivariate meta-analysis of regression coefficients and the so-called synthesis analysis, and the aim of which is to combine in a single predictive model, information from different variables. The estimator proposed in this work can increase the usefulness of these methods providing better results, as seen by application in a publicly available dataset. Source code is provided in the Appendix and in http://www.compgen.org/tools/regression.展开更多
Summetor is an operator used in the mathematics to calculate the special numbers like binomial coefficients and combinations of group elements. It has many applications in algebra, matrices like calculation of pascal ...Summetor is an operator used in the mathematics to calculate the special numbers like binomial coefficients and combinations of group elements. It has many applications in algebra, matrices like calculation of pascal triangle elements and pascal matrix formation, etc. This paper explains about its functions and properties of N-Summet-k. The result of variation between N and k is shown in tabulation.展开更多
基金the Beijing Municipal Scienceand Technology Project (No.KM202111417006)the Academic Research Projects of Beijing Union University (Nos.ZK10202305 and ZK80202004)the Beijing Municipal Science and Technology Project (No.KM202111417005)。
文摘Due to the diversity of work requirements and environment,the number of degrees of freedom(DOFs)and the complexity of structure of industrial robots are constantly increasing.It is difficult to establish the accurate dynamical model of industrial robots,which greatly hinders the realization of a stable,fast and accurate trajectory tracking control.Therefore,the general expression of the constraint relation in the explicit dynamic equation of the multi-DOF industrial robot is derived on the basis of solving the Jacobian matrix and Hessian matrix by using the kinematic influence coefficients method.Moreover,an explicit dynamic equation with general constraint relation expression is established based on the Udwadia-Kalaba theory.The problem of increasing the time of establishing constraint relationship when the multi-DOF industrial robots complete complex task constraints is solved.With the SCARA robot as the research object,the simulation results show that the proposed method can provide a new idea for industrial robot system modeling with complex constraints.
基金supported in part by the National Natural Science Foundation of China under Grant No.70903068
文摘This paper establishes the relation between APLs and direct input coefficients through Sherman-Morrison formulation.On such a basis,elasticity matrix can be calculated for each element of the APLs matrix,which measures the percentage change in the APLs-matrix element brought by one percentage change in every direct input coefficient.Hence,the percentage change in each APLs-matrix element caused by the real percentage change in each coefficient with other coefficients fixed can be drawn,from which it is easily to find out the APLs-important coefficients and is useful to explain the reason for change in the matrix.The empirical application studies the Chinese economy.What's more,the method is applied under different level of aggregation.The comparison between the APLs matrix of 1997 and 2002 allows the authors to visualize the elements that change dramatically.Then the methodology above is applied to explain the change from the perspective of direct input coefficients and find out the important coefficients to the Chinese APLs matrix.
文摘The concepts of local correlation coefficient, local canonical correlation coefficients and local canonical variables of groups of random variables are defined, which generalize the classical concepts in two groups of random variables.These concepts together with total corresponding concepts clarify the correlativity among groups of random variables.
文摘In many applications, such as in multivariate meta-analysis or in the construction of multivariate models from summary statistics, the covariance of regression coefficients needs to be calculated without having access to individual patients’ data. In this work, we derive an alternative analytic expression for the covariance matrix of the regression coefficients in a multiple linear regression model. In contrast to the well-known expressions which make use of the cross-product matrix and hence require access to individual data, we express the covariance matrix of the regression coefficients directly in terms of covariance matrix of the explanatory variables. In particular, we show that the covariance matrix of the regression coefficients can be calculated using the matrix of the partial correlation coefficients of the explanatory variables, which in turn can be calculated easily from the correlation matrix of the explanatory variables. This is very important since the covariance matrix of the explanatory variables can be easily obtained or imputed using data from the literature, without requiring access to individual data. Two important applications of the method are discussed, namely the multivariate meta-analysis of regression coefficients and the so-called synthesis analysis, and the aim of which is to combine in a single predictive model, information from different variables. The estimator proposed in this work can increase the usefulness of these methods providing better results, as seen by application in a publicly available dataset. Source code is provided in the Appendix and in http://www.compgen.org/tools/regression.
文摘Summetor is an operator used in the mathematics to calculate the special numbers like binomial coefficients and combinations of group elements. It has many applications in algebra, matrices like calculation of pascal triangle elements and pascal matrix formation, etc. This paper explains about its functions and properties of N-Summet-k. The result of variation between N and k is shown in tabulation.
