Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Minghou Cheng"'
Publikováno v:
Sultan Qaboos University Journal for Science, Vol 17, Iss 1, Pp 30-43 (2012)
Based on the idea of maximum determinant positive definite matrix completion, Yamashita proposed a sparse quasi-Newton update, called MCQN, for unconstrained optimization problems with sparse Hessian structures. Such an MCQN update keeps the sparsity
Externí odkaz:
https://doaj.org/article/beeefb66aa75447fafb3a7b34dd70c4d
Autor:
Senhua Dong, Jinyu Zhang, Dake Wu, Zhenya Zhou, Liu Yang, Qiang Liu, Minghou Cheng, Xiaolue Lai, Yan Wang
Publikováno v:
2022 IEEE 16th International Conference on Solid-State & Integrated Circuit Technology (ICSICT).
Publikováno v:
2021 IEEE 14th International Conference on ASIC (ASICON).
Publikováno v:
ACM Great Lakes Symposium on VLSI
With the increasing complexity of integrated circuits, it is becoming cumulatively challenging to solve the entire large-scale nonlinear algebraic system in DC analysis within reasonable simulation time and without accuracy lost. For this reason, we
Autor:
Minghou Cheng, Yu-Hong Dai
Publikováno v:
Science China Mathematics. 53:2907-2915
The two-sided rank-one (TR1) update method was introduced by Griewank and Walther (2002) for solving nonlinear equations. It generates dense approximations of the Jacobian and thus is not applicable to large-scale sparse problems. To overcome this di
Publikováno v:
Asia-Pacific Journal of Operational Research. 30(03):1340003-1
In this paper, we introduce a geometric model for linear symmetric eigenvalue problem, which is motivated by the fact that any eigenvalue of a symmetric positive definite matrix A is the reciprocal of the square length of an axis of the ellipsoid xTA
Publikováno v:
Sultan Qaboos University Journal for Science, Vol 17, Iss 1, Pp 30-43 (2012)
Based on the idea of maximum determinant positive definite matrix completion, Yamashita proposed a sparse quasi-Newton update, called MCQN, for unconstrained optimization problems with sparse Hessian structures. Such an MCQN update keeps the sparsity