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What is Bayesian Optimization Approach For Analog Circuit Synthesis Using Neural Network about?

This paper presents a Bayesian optimization approach for analog circuit synthesis using a neural network, which enhances the traditional Gaussian process regression model by allowing automatic learning of kernel functions from data. The proposed method improves prediction accuracy and reduces computational complexity, achieving efficient optimization with lower simulation requirements. The effectiveness of this approach is validated through real-world analog circuit applications.

Author

parthiv

Language

EN