基于神经网络动力系统DEM高程微分方程内插方法研究

Study on Neural Network Method in Power System Based on DEM Height Differential Equation

分析了DEM神经网络的基本问题,对神经网络动力系统进行多层感知,形成DEM高程微分方程内插算法,从而能够在图像修复、语音识别、控制工程领域得到应用。通过高程微分方程的动态对象分析,可以对数据聚类,形成系统模型优化方案,保证网络性能得到优化。

The basic problems in DEM neural network are analyzed, and multilayer perception is made in the neural network dynamic system. The interpolation algorithm for height differential e- quation is formed, and is applied into image restoration, speech recognition, and control engi- neering. Data clustering can be realized by an analysis to the dynamic objects of height differential equation, and the optimized scheme for system model can he formed to guarantee the optimization of the network performance.