We consider a class of ABS type algorithms for solving system of linear inequalities, where the number of inequalities does not exceed the number of variables.
The bounded parameter estimation problem and its solution lead to moie meaningful results. Its superior performance is due to the fact that the new method guarantees that the effect of the uncertainties will never be ...The bounded parameter estimation problem and its solution lead to moie meaningful results. Its superior performance is due to the fact that the new method guarantees that the effect of the uncertainties will never be unnecessarily overestimated.We then consider how to update and downdate the bounded parameter estimation problem. When updating and downdating of SVD are used to the new problem, special technologies are taken to avoid forming U and V explicitly, then increase the algorithm performance. Because of the link between the bounded parameter estimation and Tikhonov regularization procedure, we point out that our algorithms can also be used to modify regularization problem.展开更多
基金Work supported by the Science Foundation of State Education Commission of China and CNR of Italy.
文摘We consider a class of ABS type algorithms for solving system of linear inequalities, where the number of inequalities does not exceed the number of variables.
文摘The bounded parameter estimation problem and its solution lead to moie meaningful results. Its superior performance is due to the fact that the new method guarantees that the effect of the uncertainties will never be unnecessarily overestimated.We then consider how to update and downdate the bounded parameter estimation problem. When updating and downdating of SVD are used to the new problem, special technologies are taken to avoid forming U and V explicitly, then increase the algorithm performance. Because of the link between the bounded parameter estimation and Tikhonov regularization procedure, we point out that our algorithms can also be used to modify regularization problem.
