基于结构的神经网络模型

Model of neural network based on system architecture

提出了一种基于结构的神经网络模型,并介绍了利用该模型进行系统建模与参数优化的方法. 该神经网络模型本质上是结构化的,网络模型的结构与系统结构相对应,网络中神经元的个数是确定的,神经元之间的连接不是盲目的,而是根据子系统间的相互作用关系连接而成,网络的部分连接权值与系统结构参数相对应,具有明确的物理意义,所以,建模后可进一步进行结构参数的优化.

A model of neural network based on system architecture is presented, and the technique of using this type of neural networks in modeling and parameter optimization is introduced in detail. This network model is structurized in essence. The architecture of network is corresponding to that of the system. Hence, the number of neurons in network is definitive, and the neurons are connected according to the relationship among its subsystems. Parts of the weights in network, which are corresponding to the structure parameters of system, have obvious physical meanings. So further optimization of system structure parameters can be made after modeling.