Cloning DRASiW systems via memory transfer

DRASiW is an extension of the WiSARD Weightless Neural Network (WNN) model with the capability of storing the frequencies of seen patterns during the training phase in an internal data structure called “mental image” (MI). Due to this capability, in a previous work it was demonstrated how to reversely process MIs in order to generate synthetic prototypes. Then, a training set composed of synthetic prototypes can be used to train new DRASiW systems (clones) with different architectures. In this paper we present a methodology to transfer memory between DRASiW systems, and we show how it is possible to generate clones of DRASiW systems with good classification capabilities within an acceptable loss of accuracy.