Abstract
The application of feedforward neural networks in micromachined acceleration sensors are discussed. Static and dynamic sensor identification is performed to improve the performance of neural, open- and closed-loop transducers. Simulation of the performance of the transducers indicated an extended measurement range compared to the `off-the-shelf' sensors.
| Original language | English |
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| Title of host publication | Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000. IJCNN 2000 |
| Publisher | IEEE |
| Pages | 353-358 |
| Number of pages | 6 |
| ISBN (Print) | 0-7695-0619-4 |
| Publication status | Published - 2000 |
| Event | International Joint Conference on Neural Networks: Neural Computing: New Challenges and Perspectives for the New Millennium - Como, Italy Duration: 27 Jul 2000 → 27 Jul 2000 |
Conference
| Conference | International Joint Conference on Neural Networks |
|---|---|
| Abbreviated title | IJCNN 2000 |
| Country/Territory | Italy |
| City | Como |
| Period | 27/07/00 → 27/07/00 |
Keywords
- Closed loop control systems
- Computer simulation
- Control system analysis
- Control system synthesis
- Identification (control systems)
- Intelligent materials
- Sensors
- Transducers
- Feedforward neural networks
- Open loop control systems