Nuno C.G. Horta

Frederico A.E. Rocha

Ricardo M.F. Martins

Nuno C.C. Lourenço

This book applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this book presents an approach to enhance a state-of-the-art layout-aware circuit-level optimizer (GENOM-POF), by embedding statistical knowledge from an automatically generated gradient model into the multi-objective multi-constraint optimization kernel based on the NSGA-II algorithm. The results showed allow the designer to explore the different trade-offs of the solution space, both through the achieved device sizes, or the respective layout solutions.

Electronic Design Automation of Analog ICs combining Gradient Models with Multi-Objective Evolutionary Algorithms

João Leitão

Rui Ferreira Neves

This book describes a new pattern discovery approach based on the combination among rules between Perceptually Important Points (PIPs) and the Symbolic Aggregate approximation (SAX) representation optimized by Genetic Algorithm (GA). The proposed approach was tested with real data from S&P500 index and all the results obtained outperform the Buy&Hold strategy. Three different case studies are presented by the authors.

Nuno C.G. Horta

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