The aim of the paper is to present a fuzzy method for the optimization of the CMOS operational amplifier design. Our method uses f u z v sytems or fuzzy sets in all stages involved in the optimization process. In order to reduce the time spent for circuit performance evaluation, we use fuzzy system to model each circuit performance. The optimization problem formulation is accomplished in a flexible manner using fuzzy sets to delne fuzzy optimization objectives. We use qualitative design knowledge to modi& the design parameters in each iteration. This is done using a fuzzy system for each parameter, AJer introducing our fizzy optimization method we design a basic two-stage CMOS operational amplijier.
In this paper a fuzzy hierarchical approach to medical diagnosis is presented. It differs from other fuzzy medical diagnosis approaches by at least two important characteristics. First, it operates having as output universe of discourse the possibility degree of a certain diagnosis and not the diagnosis itselJ and, second, it offers some specgfic methods of dealing with a large verity of uncertainties involved by a diagnosis. The system we propose is based on diagnosis cells (elementary cells) that, depending upon the type of knowledge, can be fuzzy inference systems, neural networks, neuro-fuzzy networks, other type of hybrid systems or even simple fuzzy or crisp mathematical formulas. Applications based on this approach revealed good diagnosis performances.
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