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In this paper, we propose a modified HS conjugate gradient method which possesses the following properties (1)the sufficient descent property holds without any line searches; (2)this method inherits an important property of Hestenses- Stiefel(HS) method; (3)under some assumable conditions the method is globally convergent. Preliminary numerical results show that this method is very efficient.
A new memory gradient method for nonlinear equations is proposed. The method is an iterative method, it makes use of the current and previous iterations information to generate a new iteration. This makes the method more stable and more practical. The global convergence of the algorithm is on proved in the paper. Numerical experiments show the algorithm is efficient in many situations.
In an ad-hoc wireless network with mobile nodes, we consider communication links, which are not only used for data transfer, but which also are have the capability of link-length-measurements. We propose a method for localizing the whole network without the need of any anchor or a priori reference information. In other words, the network uses itself as an infrastructure for localization. It is shown...
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