Test generation based diagnosis of device parameters for analog circuits
Proceedings of the conference on Design, automation and test in Europe
Statistical Parameter Identification of Analog Integrated Circuit Reverse Models
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
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An accurate and efficient parameter extraction methodology, utilizing a new technique called recursive inverse approximation (RIA), is proposed for statistical modeling of integrated circuits. The main features of RIA are (1) linear approximation is used to obtain initial model parameter estimates, (2) reverse verification performs accuracy checking, and (3) error correction functions are constructed in the extracted parameter space to recursively refine the previously extracted parameter values. As a result, an approximate inverse mapping from the measured performance space to the model parameter space is established for statistical parameter extraction. Examples of parameter extraction for MOS transistors and IC multiplier block demonstrate high efficiency and accuracy of the new method