Computational Intelligence in Analog Circuits Design

This paper presents an optimization algorithm based on computational intelligence techniques, applied to the design of analog circuits. Our approach combines the best qualities of these techniques. Fuzzy sets assure the desired flexibility for the objective functions and a known range of objective function values. High accuracy and low computational complexity are simultaneously present in the neuro-fuzzy models of performances. A powerful global optimization engine is implemented by means of a genetic algorithm. Finally, the proposed algorithm is validated by the design optimization of a CMOS amplifier.

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