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Knowledge based neural network modeling of dual band PIFA

机译:基于知识的双波段PIFA神经网络建模

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摘要

In this paper, a more compact dual band planar inverted-F antenna (PIFA) has been proposed. Dual band is achieved by inserting slots on the top radiating patch. The size of the patch is 15 × 12 mm2 and finite ground plane size is 44 × 40 mm2 which can easily be integrated inside the mobile phone. The proposed antenna is simulated using CST software and simulated S11, radiation patterns are presented. The broadside radiation characteristics are achieved at both the frequency bands. Finally surface current distributions are analyzed and parametric studies of the slots dimensions are done. Two degrees of freedom is achieved to tune both the frequencies. By parametric studies of the slot parameters, it can be used for DCS, PCS, UMTS, Bluetooth and additional band (4-5 GHz) applications. Finally, Knowledge based neural network (KBNN) is used to model the resonant frequencies of the compact dual-band PIFA. The KBNN results are compared with the CST simulation results and are found to be in good accord.
机译:在本文中,提出了一种更紧凑的双频带平面倒F天线(PIFA)。通过在顶部散热片上插入插槽来实现双频。贴片的尺寸为15×12 mm 2 ,有限的接地平面尺寸为44×40 mm 2 ,可以轻松集成到手机内部。拟议的天线使用CST软件进行了仿真,并通过仿真S11给出了辐射图。在两个频带上都实现了宽边辐射特性。最后,分析了表面电流分布并完成了槽尺寸的参数研究。实现了两个自由度来调谐两个频率。通过对时隙参数的参数研究,可以将其用于DCS,PCS,UMTS,蓝牙和其他频段(4-5 GHz)应用。最后,基于知识的神经网络(KBNN)用于对紧凑型双频带PIFA的谐振频率进行建模。将KBNN结果与CST模拟结果进行比较,发现结果非常吻合。

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