Robustness of convergence in finite time for linear programming neural networks
Copyright policy )Robustness of convergence in finite time for linear programming neural networks
AbstractA recent work has introduced a class of neural networks for solving linear programming problems, where all trajectories converge toward the global optimal solution in finite time. In this paper, it is shown that global convergence in finite time is robust with respect to tolerances in the electronic implementation, and an estimate of the allowed perturbations preserving convergence is obtained. Copyright © 2006 John Wiley & Sons, Ltd.
- University of Siena Italy
convergence, linear programming, robustness, neural networks, Approximation methods and heuristics in mathematical programming, Neural network, 510, 004, Convergence; Linear programming; Neural networks; Robustness, Linear programming, Convergence, Robustness
convergence, linear programming, robustness, neural networks, Approximation methods and heuristics in mathematical programming, Neural network, 510, 004, Convergence; Linear programming; Neural networks; Robustness, Linear programming, Convergence, Robustness
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!