This paper compares and contrasts recent nonlinear behavioral modeling techniques designed for microwave and RFIC application which arise in radio and communication systems, and in the design of broad-band nonlinear components used for microwave instrumentation. These techniques include dynamic neural networks and nonlinear time series models in the time-domain, nonlinear describing functions in the frequency domain, and envelope-based methods in mixed time and frequency domains. Approaches to generating these models from both simulation and nonlinear microwave measurements are reviewed.
Published in:
Design Automation Conference, 2003. Proceedings
Date of Conference: 2-6 June 2003