基于带宽剩余率的脉冲耦合神经网络最短路径算法

利用脉冲耦合神经网络（pulse coupled neural network, PCNN）寻找最短路径是一种非确定性算法，运算的复杂度只和最短路径的长度有关，和路径图的复杂程度无关。已有的PCNN最短路径算法只考虑路径长度，而未考虑其他参数，如带宽和时延等。这里除了考虑路径长度，同时考虑实际中带宽剩余量对网络的影响，提出了一种基于带宽剩余率的最短路径算法，用带宽剩余率参数来控制神经元阈值，寻找最短路径。仿真结果表明，该算法可以寻找到全局最优解。

PCNN shortest path algorithm based on bandwidth remaining rate

Using pulse coupled neural network (PCNN) to find a shortest path is a non-deterministic algorithm . The computation complexity is only related to the shortest path’s length, and is not related to the complexity of the path graph. The existing PCNN finding shortest path algorithm only takes into account the path length, without considering other parameters. This paper proposes an algorithm based on the bandwidth remaining rate, which considers the influence of the bandwidth remaining amount on the network, as well as the path length; besides, parameter of the bandwidth remaining rate is used to control neurons’ threshold to find the shortest path. The simulation results show that this method can find the global optimal solution.