A Machine-Learning-Based Method to Accelerate the Design of SAW Filters at Different Frequency Bands-Reference-Cited by-同舟云学术

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A Machine-Learning-Based Method to Accelerate the Design of SAW Filters at Different Frequency Bands

Published:2024-08-15 Issue:16 Volume:24 Page:26971-26981
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Hou Xuanying¹^ORCID,Hu Hao-Jie¹,Xiao Li-Ye²^ORCID,Chen Ke¹^ORCID,Zhuang Mingwei¹^ORCID,Huo Liu Qing³

Affiliation:

1. Institute of Electromagnetics and Acoustics, Fujian Provincial Key Laboratory of Electromagnetic Wave Science and Detection Technology, Xiamen University, Xiamen, China

2. Department of Electronic Science and Engineering, Institute of Electromagnetics and Acoustics, Xiamen University, Xiamen, China

3. Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA

Funder

National Natural Science Foundation of China

President’s Fund of Xiamen University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7361/10637303/10594722.pdf?arnumber=10594722

Reference25 articles.

1. SAW Microsensor Brain Implant for Prediction and Monitoring of Seizures

2. Noise Radar Approach for Interrogating SAW Sensors Using Software Defined Radio

3. Equivalent Circuit Models for SAW Delay Line Sensors

4. A wideband multi-mode SAW filter employing pitch-modulated IDTs on cu-grating/15°YX-LiNbO3-substrate structure

5. P6G-2 Synthesis of Frequency Response for Wideband SAW Ladder Type Filters

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