Artificial neural networks for rf and microwave design-from theory to practice
Carleton University · University of Colorado Boulder
Abstract
Neural-network computational modules have recently gained recognition as an unconventional and useful tool for RF and microwave modeling and design. Neural networks can be trained to learn the behavior of passive/active components/circuits. A trained neural network can be used for high-level design, providing fast and accurate answers to the task it has learned. Neural networks are attractive alternatives to conventional methods such as numerical modeling methods, which could be computationally expensive, or analytical methods which could be difficult to obtain for new devices, or empirical modeling solutions whose range and accuracy may be limited. This tutorial describes fundamental concepts in this emerging…
Citation impact
- FWCI
- 18.06
- Percentile
- 100%
- References
- 32
Authors
3Topics & keywords
- Artificial neural network
- Computer science
- Electronic engineering
- Artificial intelligence
- Microwave
- Computer engineering
- Machine learning
- Engineering