Calculation of fractional derivatives of noisy data with genetic algorithms
This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with...
| Autor principal: | |
|---|---|
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2014
|
| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.22/4314 |
| País: | Portugal |
| Oai: | oai:recipp.ipp.pt:10400.22/4314 |
| Resumo: | This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established. |
|---|