Abstract
Artificial neural networks have been used as an important technique in microwave modelling and optimisation. This paper gives an overview and recent developments on the knowledge-based neural modelling techniques in microwave modelling and design. The knowledge-based artificial neural networks are constructed by incorporating the existing knowledge such as empirical formulas, equivalent circuit models and semi-analytical equations in neural network structures. When one of the knowledge-based methods can not provide sufficient accuracy, two of them can be used in the same modelling process. This combination of methods is named hybrid technique. Using knowledge-based techniques requires less training data and has better extrapolation performance than classical neural networks. The advantages of using knowledge-based neural network modelling are demonstrated with microwave device modelling applications.
| Original language | English |
|---|---|
| Pages (from-to) | 213-228 |
| Number of pages | 16 |
| Journal | International Journal of Mathematical Modelling and Numerical Optimisation |
| Volume | 2 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Apr 2011 |
Keywords
- Computer-aided design
- KBNN
- Knowledge-based neural networks
- Mathematical modelling
- Microwave devices