Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A mixed-integer nonlinear programming approach to analog circuit synthesis
DAC '92 Proceedings of the 29th ACM/IEEE Design Automation Conference
DARWIN: CMOS opamp synthesis by means of a genetic algorithm
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Toward Analog Circuit Synthesis: A Global Methodology Based upon Design of Experiments
SBCCI '00 Proceedings of the 13th symposium on Integrated circuits and systems design
Synthesis of CMOS Operational Amplifiers through Genetic Algorithms
SBCCI '98 Proceedings of the 11th Brazilian Symposium on Integrated circuit design
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A new method based on adaptive GA(genetic algorithm) for optimizing the parameters of CMOS operational amplifier is presented in this paper. The synthesis of the Op-amp (operational amplifier) can be translated into multiple-objective optimization task, in which a large number of specifications have to be taken into account. Such as DC-gain, bandwidth of unity gain, phase-margin, power, noise and others. The feature of the method is that combining the skills of manual experience of analog circuits design and genetic algorithm, through adjusting the GA with the evolution process, the problems of convergence and multiple objective optimization tasks can be solved; and operational amplifiers for different use can be designed depending on various performance specifications. The results of groups of simulation show that this method can optimize the parameters of analog circuits accurately and efficiently.