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首页> 外文期刊>IEEE Transactions on Microwave Theory and Techniques >Combined Use of Genetic Algorithms and Gradient Descent Optmization Methods for Accurate Inverse Permittivity Measurement
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Combined Use of Genetic Algorithms and Gradient Descent Optmization Methods for Accurate Inverse Permittivity Measurement

机译:遗传算法和梯度下降优化方法的组合使用,用于精确的反介电常数测量

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摘要

A novel inverse transmission-line method for the complex permittivity determination of arbitrary shaped materials is presented. Complex permittivity is inferred by using an inverse calculation procedure, which is based on a combined optimization strategy of both genetic algorithms and the gradient descent method. The optimization procedure matches the measured and simulated complex scattering parameters' frequency behavior of materials within a WR340 waveguide. High accuracy and practical suitability are validated through experimental tests. The dielectric properties of PTFE and epoxy resin mixed with iron-oxide-doped fiberglass have been measured for different shapes and positions. Dielectric multilayer structures have been used to demonstrate that this technique is able to measure the individual permittivity of each element of the structure. Both two- and three-dimensional approaches have been carried out and their advantages and drawbacks discussed.
机译:提出了一种新颖的反传输线方法,用于确定任意形状的材料的复介电常数。复介电常数是通过使用逆计算程序来推断的,该程序基于遗传算法和梯度下降方法的组合优化策略。优化过程与WR340波导中材料的实测和模拟复杂散射参数的频率行为相匹配。通过实验测试验证了高精度和实用性。对于不同的形状和位置,已经测量了PTFE和环氧树脂与掺有氧化铁的玻璃纤维混合的介电性能。介电多层结构已被用来证明该技术能够测量结构中每个元素的介电常数。已经进行了二维和三维方法,并讨论了它们的优缺点。

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