LTCC滤波器的空间映射神经网络建模

H. Xia, Z. Q. Xu, P. Wang, L. Jin
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引用次数: 1

摘要

低温共烧陶瓷(LTCC)滤波器的建模与分析、优化与合成是低温共烧陶瓷滤波器设计中的主要问题。提出了一种基于空间映射神经建模方法的多层滤波器。通过优化和训练滤波器中三维结构与等效电路之间的映射关系,可以准确、快速地得到滤波器的物理结构特性。通过实际LTCC过程验证了该模型的有效性。该滤波器具有300 MHz的通频带,中心频率为2.45 GHz,带内插入损耗为2.2 dB。实测结果与高频仿真结果吻合较好。该建模方法可用于LTCC微波无源器件的设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling of LTCC filter using space-mapping neural network method
Modeling and analysis, optimization, and synthesis are the issues in design of low temperature co-fired ceramic (LTCC) filters. A multilayer filter is proposed based on the space mapped neuromodeling method. With optimizing and training the mapped relations between 3D structure and equivalent circuit in filter, physical structural characteristics of the filter can be got accurately and rapidly. This proposed model is validated through actual LTCC process. The filter exhibits a 300 MHz passband with the center frequency at 2.45 GHz and an in-band insertion loss of 2.2 dB. Measured results agree well with the high frequency simulation. The modeling method can be used for design on LTCC microwave passive components.
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