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Design and research of RFID microstrip antenna based on improved PSO neural networks

机译:基于改进PSO神经网络的RFID微带天线的设计与研究

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There are some key parameters in RFID reader antenna which are related closely with the antenna structure, such as resonant frequency, return loss and bandwidth in the antenna design process. Structure and properties of the antenna is a complex nonlinear system with complex state which is difficult to make mode by the mathematic method. In this case, neural network is used to express the nonlinear system in this article. Giving a large number of simulation data for the samples, adaptive particle swarm algorithm is used to train network by simulation experiment which is used to verify the fitting degree of neural networks and simulation results. The experiment result shows that PSO neural network can improve the level of computer-aided design of micro strip antenna and achieve the antenna design quickly.
机译:RFID阅读器天线中有一些与天线结构密切相关的关键参数,例如天线设计过程中的谐振频率,回波损耗和带宽。天线的结构和特性是一个复杂的非线性系统,具有复杂的状态,很难通过数学方法建立模式。在这种情况下,本文使用神经网络来表示非线性系统。在给出大量仿真数据的基础上,采用自适应粒子群算法通过仿真实验对网络进行训练,以验证神经网络的拟合程度和仿真结果。实验结果表明,PSO神经网络可以提高微带状天线的计算机辅助设计水平,并能快速实现天线设计。

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