Robustizing circuit optimization using Huber functions

The authors introduce a novel approach to ´robustizing´ microwave circuit optimization using Huber functions, both two-sided and one-sided. They compare Huber optimization with l/sub 1/, l/sub 2/, and minimax methods in the presence of faults, large and small measurement errors, bad starting points, and statistical uncertainties. They demonstrate FET statistical modeling, multiplexer optimization, analog fault location, and data fitting. They extend the Huber concept by introducing a ´one-sided´ Huber function for large-scale optimization. For large-scale problems, the designer often attempts, by intuition, a preliminary optimization by selecting a small number of dominant variables. It is demonstrated, through multiplexer optimization, that the one-sided Huber function can be more effective and efficient than minimax in overcoming a bad starting point.<>