X. Zhu, S. Khatri, and P. Parrilo. with linear cuts: upper bound computation. In Proceedings of the American Control Conference, pages 2370--2374, 1999.  Home/Search   Document Details and Download   Summary   Related Articles

....aligned cuts in the standard B B algorithm, the number of branches required to get to certain level of accuracy grows exponentially with the number of parameters. However, a linear cut along this hyperplane solves the problem immediately. This is the motivation for studying with linear cuts([9]) and applying the linear cut method to computing bounds for probabilistic ( 7] The probabilistic upper bound obtained by the linear cut method is exact for the rankone problems. For problems that are close to rank one, the linear cut algorithm outperforms the B B algorithm in getting tighter ....

....in the next section. 4 The Linear Cut (LC) Algorithm The need to compute the probabilistic upper bound for rank one problems motivated the research of with uncertainty in more exotic regions than the standard 1 norm bounded set, for example, spherical , elliptical ( 3] and with linear cuts([9]) In particular, with linear cuts deals with the real parametric uncertainty with the linear constraint jc T ffij 1, where ffi = ffi 1 ; ffi 2 ; Delta Delta Delta ; ffi n ] T is the vector of the parameters, and c = c 1 ; c 2 ; Delta Delta Delta ; c n ] T 2 R n is the constant ....

[Article contains additional citation context not shown here]

X. Zhu, S. Khatri, and P. Parrilo. with linear cuts: upper bound computation. In Proceedings of the American Control Conference, pages 2370--2374, 1999.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC