Learning Online MEMS Calibration with Time-Varying and Memory-Efficient Gaussian Neural Topologies

This work devised an on-device learning approach to self-calibrate Micro-Electro-Mechanical Systems-based Inertial Measurement Units (MEMS-IMUs), integrating a digital signal processor (DSP), an accelerometer, and a gyroscope in the same package. The accelerometer and gyroscope stream their data in...

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Bibliographic Details
Main Authors: Danilo Pietro Pau, Simone Tognocchi, Marco Marcon
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/25/12/3679
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