论文信息 - Definition of an energy function for the random neural to solve optimization problems.

Definition of an energy function for the random neural to solve optimization problems.

In this paper, we propose a general energy function for a new neural model, the random neural model of Gelenbe. This model proposes a scheme of interaction between the neurons and not a dynamic equation of the system. We then apply this general energy function on different optimization problems: the graph partitionning problem and the minimum node covering problem.

Aguilar Jose

[1] Stephen Grossberg,et al. Nonlinear neural networks: Principles, mechanisms, and architectures , 1988, Neural Networks.

[2] Gene A. Tagliarini,et al. Optimization Using Neural Networks , 1991, IEEE Trans. Computers.

[3] Erol Gelenbe,et al. Learning in the Recurrent Random Neural Network , 1992, Neural Computation.

[4] Erol Gelenbe,et al. Minimum Graph Covering with the Random Neural Network Model , 1992 .

[5] Erol Gelenbe,et al. Random Neural Networks with Negative and Positive Signals and Product Form Solution , 1989, Neural Computation.

[6] Erol Gelenbe,et al. Stability of the Random Neural Network Model , 1990, Neural Computation.