Abstract:
A network sensitivity figure for use in gradient-type optimizers which accounts for random parameter variations encountered during manufacturing is introduced. The differ...View moreMetadata
Abstract:
A network sensitivity figure for use in gradient-type optimizers which accounts for random parameter variations encountered during manufacturing is introduced. The difference between conventional sensitivity descriptions and the authors' sensitivity figure is analyzed and explained. Two examples are presented where yield improvement is obtained using the new sensitivity figure in a gradient-type optimizer.<
>
Published in: IEEE Transactions on Microwave Theory and Techniques ( Volume: 36, Issue: 2, February 1988)
DOI: 10.1109/22.3530