@inproceedings{601669ff081e49259b97a9f1ab3d7e80,
title = "Neural network based compensation of micromachined accelerometers for static and low frequency applications",
abstract = "In this work, a single-shot direct inverse compensation procedure based on neural networks is proposed, with application to micromachined accelerometers. Compensation was first considered from an empirical viewpoint to determine whether or not some kind of relationship exists between the severity of different nonlinearities and the complexity of the network required to control such nonlinearities. The procedure was then validated by applying direct inverse control to the measured static characteristic of a micromachined acceleration sensing element.",
keywords = "SYSTEMS",
author = "Elena Gaura and Rider, {R. J.} and N Steele",
year = "2000",
doi = "10.1007/3-540-45049-1_63",
language = "English",
isbn = "3540676899",
series = "Lecture Notes in Artificial Intelligence",
publisher = "Springer, Springer Nature",
pages = "534--542",
editor = "Rasiah Loganantharaj and Gunther Palm and Moonis Ali",
booktitle = "Intelligent Problem Solving. Methodologies and Approaches",
address = "United States",
note = "13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2000) ; Conference date: 19-06-2000 Through 22-06-2000",
}