Conference paper
A neural flow estimator
In
Proceedings of the Ieee Instrumentation and Measurement Technology Conference
—
1995, pp. 385-385
Abstract
This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system is implemented using switched-current technique and is capable of estimating flow in the μl/s range.
The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V with a total current consumption of 2 mA, resulting in a power consumption of 10 mW. The dimensions of the clip core are 3 mm×4.5 mm
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 1995 |
| Pages: | 385-385 |
| Proceedings: | 1995 IEEE Instrumentation and Measurement Technology Conference |
| Journal subtitle: | Integrating Intelligent Instrumentation and Control |
| ISBN: | 0780326156 and 9780780326156 |
| Types: | Conference paper |
| DOI: | 10.1109/IMTC.1995.515299 |
| ORCIDs: | Jørgensen, Ivan Harald Holger and Bruun, Erik |
