基于局部条件的资源分配网络及其在非线性系统预测中的应用

Wenyuan Qi, Dazi Li, Q. Jin
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引用次数: 0

摘要

针对无线局域网存在的问题,本文提出了一种基于局部条件的资源分配网络(RAN- lc)。该方法利用K-means聚类算法和激活函数的特性得到初始隐藏节点,并利用基于局部条件的新颖性准则取代旧的新颖性准则,保持网络的整洁和高效。此外,该方法采用多模式,提高了网络在参数调整状态下的泛化能力。仿真结果表明,该方法能够快速、合理地生成网络。最终生成的网络具有良好的性能,在非线性系统的预测中也有很好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A resource-allocating network based on local conditions and its application in prediction of nonlinear systems
In this paper, a resource-allocating network based on local conditions (RAN-LC) is proposed to avoid the existing problems of RAN. This method gets the initial hidden nodes by using K-means clustering algorithm and the characteristics of activation function, and it utilizes new Novelty Criterion based on local conditions instead of the old one to keep the network neat and efficient. Moreover, it adopts Multi-patterns to enhance the generalization ability of network in the state of parameters adjustment. The simulation results show that this method can generate network quickly and more reasonable. The network generated finally has good performance and also works well in the prediction of nonlinear systems.
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