Figure 2 - available via license: Creative Commons Attribution 4.0 International
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The flowchart illustrates our design process for optimizing geometric parameters. It involves two stages: the ANN modeling stage and the reinforcement learning stage.
Source publication
Microstrip filters are widely used in high-frequency circuit design for signal frequency selection. However, designing these filters often requires extensive trial and error to achieve the desired performance metrics, leading to significant time costs. In this work, we propose an automated design flow for hairpin filters, a specific type of microst...
Context in source publication
Context 1
... shown in Figure 1, the arm lengths (L 1 , L 2 , Lt), gaps (d 1 , d 2 ), and line width (W) are all related to the frequency response of the filter, affecting its stopband attenuation and selectivity. Figure 2 illustrates the design flowchart of the optimization strategy proposed for the hairpin filter. We propose a method for designing and optimizing the hairpin filter using neural network modeling and reinforcement learning techniques. ...
