ANN based modeling, testing and diagnosis of MEMS


Litovski, V, Andrejevic, M and Zwolinski, M (2004) ANN based modeling, testing and diagnosis of MEMS. In, NEUREL 2004: SEVENTH SEMINAR ON NEURAL NETWORK APPLICATIONS IN ELECTRICAL ENGINEERING, Belgrade, Serbia, 23 - 25 Sep 2004. IEEE, 183-188.

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Description/Abstract

New concepts of simulation, testing and diagnosis of MEMS are proposed, intended to boost the time to market and dependability of such systems. Black-box modeling of non-electronic parts is introduced using artificial neural networks, so enabling radically faster simulation without concurrent algorithms and parallel computation. A Jumped model of the capacitive transducer, being the part of a micro-electro-mechanical capacitive pressure sensing system, is created using an ANN. Faults are then introduced to the sensing system and simulation of the fault-free and faulty circuits are demonstrated.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: SEP 23-25, 2004
ISBNs: 0780385470
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > EEE
ePrint ID: 263413
Date Deposited: 12 Feb 2007
Last Modified: 27 Mar 2014 20:07
Publisher: IEEE
Further Information:Google Scholar
ISI Citation Count:0
URI: http://eprints.soton.ac.uk/id/eprint/263413

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