Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes
An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault dia...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2008.
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Σειρά: | Lecture Notes in Control and Information Sciences,
377 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Modelling Issue in Fault Diagnosis
- Locally Recurrent Neural Networks
- Approximation Abilities of Locally Recurrent Networks
- Stability and Stabilization of Locally Recurrent Networks
- Optimum Experimental Design for Locally Recurrent Networks
- Decision Making in Fault Detection
- Industrial Applications
- Concluding Remarks and Further Research Directions.