In this work, we have used a novel adaptive neuro-fuzzy inference system (ANFIS) method to design and fabricate a high-performance microstrip diplexer. For developing the proposed ANFIS model, the hybrid learning method consisting of least square estimation and back-propagation (BP) techniques is utilized. To achieve a compact diplexer, a designing process written in MATLAB 7.4 software is introduced based on the proposed ANFIS model. The basic microstrip resonator used in this study is mathematically analyzed. The designed microstrip diplexer operates at 2.2GHz and 5.1GHz for wideband wireless applications. Compared to the previous works, it has the minimum insertion losses and the smallest area of 0.007 λg2 (72.2mm²). It has flat channels with very low group delays (GDs) and wide fractional bandwidths (FBWs). The GDs at its lower and upper channels are only 0.48ns and 0.76ns, respectively. Another advantage of this work is its suppressed harmonics up to 12.9GHz (5th harmonic). To design the proposed diplexer, an LC model of the presented resonator is introduced and analyzed. To verify the simulation results and the presented ANFIS method, we fabricated and measured the proposed diplexer. The results show that both simulations and measurements data are in good agreement, which give reliability to the proposed ANFIS method.

中文翻译：

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一种新的基于 ANFIS 的混合方法，用于设计和制造用于无线应用的高性能新型微带双工器

在这项工作中，我们使用了一种新颖的自适应神经模糊推理系统 (ANFIS) 方法来设计和制造高性能微带双工器。为了开发所提出的 ANFIS 模型，使用了由最小二乘估计和反向传播 (BP) 技术组成的混合学习方法。为了实现紧凑型双工器，基于所提出的ANFIS模型，介绍了用MATLAB 7.4软件编写的设计过程。对本研究中使用的基本微带谐振器进行了数学分析。设计的微带双工器工作在 2.2GHz 和 5.1用于宽带无线应用的 GHz。与前作相比，插入损耗最小，面积最小为0.007λG2(72.2毫米² )。它具有平坦的通道，具有非常低的群延迟 (GD) 和较宽的分数带宽 (FBW)。其上下通道的 GD 仅为 0.48ns 和 0.76ns，分别。这项工作的另一个优点是其抑制的谐波高达 12.9GHz（5 次谐波）。为了设计所提出的双工器，一个液相色谱介绍并分析了所提出的谐振器模型。为了验证仿真结果和所提出的 ANFIS 方法，我们制造并测量了所提出的双工器。结果表明，模拟和测量数据具有良好的一致性，这为所提出的 ANFIS 方法提供了可靠性。