Applications of Artificial Neural Networks to RF and Microwave Design

The recent applications of Artificial Neural Networks (ANN) to RF and microwave design mark the beginning of an unconventional and exciting alternative to modeling, design and optimization problems in RF, microwave and millimeter-wave CAD. ANN can learn and generalize from data allowing model development even when component formulas are unavailable. ANN models are easier to update as technology changes. ANNs are universal approximators allowing re-use of the same modeling technology for both linear and nonlinear problems and at device, circuit or system levels. Yet, ANN models are simple and model evaluation is very fast. Recent works have led to the use of ANNs for modeling microstrip
lines, vias, CPW discontinuities, spiral inductors, FETs and VLSI interconnects; for speeding up harmonic balance simulations and optimizations; and for Smith chart representation and automatic impedance matching. These pioneering works herald a brand new opportunity to handle some of the toughest RF and microwave CAD problems today and tomorrow.
This talk will review applications of ANN modeling to RF, microwave and millimeter-wave design and discuss the recent work at University of Colorado in the area of vias and multilayer interconnect modeling, CPW components, circuits, patch antennas and multilayer transmission structures and circuit design.

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Last modified: 02/03/07