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The paper presents an efficient and accurate approach for statistical analog yield optimization and variation-aware circuit sizing using computational intelligence techniques. It introduces the ordinal optimization-based random-scale differential evolution (ORDE) algorithm, which significantly enhances computational efficiency while maintaining high accuracy compared to traditional Monte-Carlo methods. The proposed method optimally allocates computational resources and improves convergence speed, making it

Author

morandotti.francesco

Language

EN