微带天线谐振频率的小波粒子群小波神经网络建模

微带天线谐振频率的小波粒子群小波神经网络建模

内容简介：谐振频率是微带天线设计过程中最重要的一个参数,直接决定设计的成败.本文基于改进的小波变异粒子群优化算法该算法的小波神经网络对矩形微带天线的谐振频率进行建模,可以有效地提高神经网络的建模精度.仿真试验表明,改进的小波变异粒子群优化算法是一种有效的方法,可以有效提高小波神经网络的泛化能力,基于该算法所建立的微带天线的谐振频率模型好于此问题的已有结论.

Abstract：Resonant frequency is an important parameter in the design process of microstrip antenna(MSA). The model of resonant frequency of rectangular MSA is established in terms of the wavelet neural network, and it can improve the model’s accuracy definitely.Experiment shows that the IPSOWM algorithm is an effect method,and it may improve the generalization ability.Moreover,the model of resonant frequency of MSA established by using the algorithm is better than available one.

作者：佘俊, 高东慧, 田雨波, 刘维亭,

关键词：微带天线, 谐振频率, 小波神经网络, 粒子群优化算法, 小波变异,