A LSTM based method to remove the time-varying errors for mm-wave microfluidic measurement
- Resource Type
- Conference
- Authors
- Ge, Fan; Wu, Zhihao; Sun, Wen; Su, Jiangtao
- Source
- 2023 16th UK-Europe-China Workshop on Millimetre Waves and Terahertz Technologies (UCMMT) Millimetre Waves and Terahertz Technologies (UCMMT), 2023 16th UK-Europe-China Workshop on. 1:1-3 Aug, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Analytical models
Measurement uncertainty
Terahertz materials
Predictive models
Stability analysis
Frequency measurement
Reliability
- Language
- ISSN
- 2639-4537
Time-varying errors bring adverse effects to the mmwave microfluidic measurement system. In this paper, a method based on LSTM model is introduced to predict the drift errors, hence the consistency can be improved and the cost of time can be reduced, especially in mm-wave band. The paper started with analyzing of drift errors source then used LSTM model to build prediction model for drift errors. Experimental result showed that this method can predict drift errors effectively and improve the reliability of long-term measurement at mm-wave frequencies.