Several improvements have been proposed in the literature for the Weightless Neural Networks (WNNs), in particular the DRASiW extension of the WiSARD model with the introduction of mental imagery and bleaching procedure. We propose a new bleaching procedure called Dynamic Adaptive Bleaching (DAB) and its variant, refined Dynamic Adaptive Bleaching (r DAB), to improve the WNNs performance in terms of computational time and classification capabilities.
Improving the DRASiW performance by exploiting its own "Mental Images"
Gianluca Coda;Massimo De Gregorio;Antonio Sorgente
;Paolo Vanacore
2023
Abstract
Several improvements have been proposed in the literature for the Weightless Neural Networks (WNNs), in particular the DRASiW extension of the WiSARD model with the introduction of mental imagery and bleaching procedure. We propose a new bleaching procedure called Dynamic Adaptive Bleaching (DAB) and its variant, refined Dynamic Adaptive Bleaching (r DAB), to improve the WNNs performance in terms of computational time and classification capabilities.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
ES2023-25.pdf
accesso aperto
Tipologia:
Versione Editoriale (PDF)
Licenza:
Dominio pubblico
Dimensione
2.02 MB
Formato
Adobe PDF
|
2.02 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
