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Analog Circuit Based on Computational Intelligence Techniques

Oltean G., Hintea S., Şipos E.

Journal of Automation Mobile Robotics and Intelligent Systems

2009

Vol. 3, No. 2

63-69

This paper presents a new method for analog circuit design optimization. Our approach turns to good account the advantages offered by computational intelligence techniques. Design objectives can be expressed in a flexible manner using fuzzy sets. This way appears the possibility to consider different degrees for requirement achievements and acceptability degree for a particular solution. Neuro-fuzzy systems (universal approximators) are used to model the complex multi-variable and nonlinear circuit performances. These models satisfy two main requirements: high accuracy and low computation complexity. An efficient and robust genetic algorithm does avoiding local minima the exploration of the large, multidimensional solution space in quest for the optimal solution.