waveguide network

Design of rectangular waveguide terminal matched load based on multilayer perceptron neural network ( MLPNN) is presented.

讨论了多层感知器神经网络（MLPNN）在矩形波导终端匹配短负载设计中的应用。

Structure-light-induced waveguide devices in PR crystals can be used for the current optical communication systems, and may be used for optical dynamic interconnection and optical neural network systems.

因此光折变晶体中结构光写入的波导器件可以被用于现有的光通信系统，并且有望被用于动态光互连以及光学神经网络系统。

Furry neural network model of capacitance parameters for CPW ( coplanar waveguide) was built.

在此基础上，用建立的模糊神经网络对微波无源器件共面波导的电容参数来进行提取。