Accurate microwave filter design based on particle swarm optimization and one‐dimensional convolution autoencoders

This paper proposes a one‐dimensional convolutional autoencoders (1D‐CAE) surrogate‐based electromagnetic (EM) optimization technique exploiting particle swarm optimization (PSO) algorithm for microwave filter design. The 1D‐CAE is a flexible neural network structure that can be used as surrogate mo...

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Veröffentlicht in:	International journal of RF and microwave computer-aided engineering Jg. 32; H. 4
Hauptverfasser:	Wang, Yanxing, Zhang, Zhuowei, Yi, Yaxin, Zhang, Yongliang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 01.04.2022
Schlagworte:	Algorithms CAD Computer aided design Design optimization Filter design (mathematics) Inverse problems Mathematical models microwave filter design Microwave filters Modelling Neural networks one‐dimensional convolutional autoencoders Optimization techniques Parameters Particle swarm optimization surrogate model
ISSN:	1096-4290, 1099-047X
Online-Zugang:	Volltext
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