With the trend from micro- to nanoelectronics the control of production deviations can not keep pace with the reduction of the absolute sizes of semiconductor devices. This results in an increased number of circuits beyond specification. The presented symbolic methods for reducing behavioral models with parameter variations assist designing and optimizing robust electronic circuits to increase the yield of produced circuits

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In this paper we introduce a robust method for the model-driven design of reduced parameter-varying analog systems. The ideas behind our approach are twofold: On the one hand we present an algorithm for decreasing the model order of large systems. It utilizes the hierarchical structure of compound systems to simplify component models while ensuring the validity of the composed model. On the other hand we announce a statistical method for reducing circuit equations with parameter variations. Combining both we generate symbolic behavioral models of real-world analog circuits under process variations. Finally, for illustrating we apply the overall procedure to the operational amplifier OpAmp 741 with varying parameters

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