Method and circuits to virtually increase the number of prototypes in artificial neural networks

A device to virtually increase a number of prototypes of a neural network, comprising:

• a neural network formed by a plurality of neurons, each neuron having a prototype memory dedicated to store a prototype and an evaluator to generate a local result of an evaluation based on a comparison between an input pattern presented to the neuron and the prototype stored therein, wherein the neural network is adapted to generate, according to at least one specified parameter and the local results, a global result corresponding to the input pattern;
• a memory coupled to the neural network and comprising a plurality of prototypes, a plurality of input patterns to be presented to the neural network, and an amount of storage space to store a predetermined number of global results, wherein each of a plurality of slices is associated with a plurality of the prototypes and wherein each slice is a subset of a set of prototypes;
• and
• a circuit coupled to the memory and configured to compare, according to predetermined criteria, a current global result from a current slice with a previously obtained global result from a previous slice, wherein both the current and previously obtained global result are determined from the same input pattern, and wherein the circuit can store a new global result in the memory based on the comparison.