一种新型的动态递归神经网络及其全自动设计算法

A NEW DYNAMIC RECURSIVE NEURAL NETWORK AND FULLY AUTOMATIC DESIGN ALGORITHM

  • 摘要: 本文基于非线形自回归滑动平均模型NARMA模型和前馈神经网络建模的思想,提出一种输入层与输出层神经元递归的动态递归神经网络;基于进化计算中遗传算法和进化策略与自寻优BP算法的不同结合方式,提出两种动态递归神经网络全自动高效设计算法,实现了网络结构、权重和自反馈增益同时优化学习,实例应用表明所提网络结构及其设计算法的有效性.

     

    Abstract: Based on the modeling idea of non-lineal auto-regressive moving average model and feedforward neural network, the new dynamic recu rsive neural network with the input and output neuron recursion is proposed. Based on the different combined ways to the genetic algorithm, evolutionary strategy and auto-optimal Back Propagation algorithm, the two fully automatic design a lgorithms for the dynamic recursive neural network are also advanced to realize high learning speed and simultaneous optimization learning of network structure, weights, and self feedback parameters. The result of the real applications hows that the new network and design algorithms are effective.

     

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