An evolutionary approach to automatic synthesis of high-performance analog integrated circuits

This paper presents an analog integrated circuit synthesis system based on an evolutionary approach. The system contains several novel features. One of these is the high-performance optimization algorithm, which is a combination of evolutionary strategies and simulated annealing. Modeling of dc parameters is done via a fast dc simulator developed for this purpose whereas modeling of ac parameters can be done either with user-defined equations or with neural-fuzzy performance models trained from SPICE simulations. Another novel feature of the system is the incorporation of matching properties of devices. This way, the optimized circuit becomes tolerant to process variations. The synthesis system has been tested on several independent examples and synthesized circuits have been verified functionally with SPICE simulations. Finally, a prototype chip composed of the three examples has been manufactured. The measurement results have demonstrated the validity of the synthesis system on silicon.