Parallel analog circuit optimization method based on genetic algorithm and machine learning
US11714943B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 13, 2019 |
| Grant date | Aug 1, 2023 |
| Priority date | — |
| Expiry date | May 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2119/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A parallel analog circuit automatic optimization method based on genetic algorithm and machine learning comprises global optimization based on genetic algorithm and local optimization based on machine learning, with the global optimization and the local optimization performed alternately. The global optimization based on genetic algorithm utilizes parallel SPICE simulations to improve the optimization efficiency while guaranteeing the optimization accuracy, combined with parallel computing. The local optimization based on machine learning establishes a machine learning model near the global optimal point obtained by the global optimization, and uses the machine learning model to replace the SPICE simulator, thus reducing the time costs brought by a large number of simulations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.