This paper proposes an intelligent system that aids the electronic designer to achieve compliance with design constraints exploiting the overwhelming set of components available on theWeb. Mainly, designing an input filter for lowering electromagnetic interference (EMI) is still a challenge since the choice of components is subjected to multiple constraints. As a matter of fact, once the components' values are known, the choice depends on the required optimization, such as minimum cost, volume, or size. The Web offers a broad set of devices, but a complete search can result in a time-consuming activity. Besides, the designer's experience often reveals crucial. The proposed system aids the designer in finding components based on the main constraints and performs an optimization. A Machine Learning algorithm learns the designer's choice to be used in future design.
Intelligent -Web search for EMI filter optimization
Giovanni Pilato;Riccardo Rizzo;Filippo Vella;Gianpaolo Vitale
2021
Abstract
This paper proposes an intelligent system that aids the electronic designer to achieve compliance with design constraints exploiting the overwhelming set of components available on theWeb. Mainly, designing an input filter for lowering electromagnetic interference (EMI) is still a challenge since the choice of components is subjected to multiple constraints. As a matter of fact, once the components' values are known, the choice depends on the required optimization, such as minimum cost, volume, or size. The Web offers a broad set of devices, but a complete search can result in a time-consuming activity. Besides, the designer's experience often reveals crucial. The proposed system aids the designer in finding components based on the main constraints and performs an optimization. A Machine Learning algorithm learns the designer's choice to be used in future design.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.