Abstract: A method of performing unsupervised detection of repeating patterns in a series (TS) of events (E21, E12, E5, . . . ), comprising the steps of: a) Providing a plurality of neurons (NR1-NRP), each neuron being representative of W event types; b) Acquiring an input packet (IV) comprising N successive events of the series; c) Attributing to at least some neurons a potential value (PT1-PTP), representative of the number of common events between the input packet and the neuron; d) Modifying the event types of neurons having a potential value exceeding a first threshold TL; and e) Generating a first output signal (OS1-OSP) for all neurons having a potential value exceeding a second threshold TF, and a second output signal, different from the first one, for all other neurons. A digital electronic circuit and system configured for carrying out the above method.

Abstract: A method of performing unsupervised detection of repeating patterns in a series (TS) of events (E21, E12, E5 . . . ), comprising the steps of: a) Providing a plurality of neurons (NRI-NRP), each neuron being representative of W event types; b) Acquiring an input packet (IV) comprising N successive events of the series; c) Attributing to at least some neurons a potential value (PTI-PTP), representative of the number of common events between the input packet and the neuron; d) Modify the event types of neurons having a potential value exceeding a first threshold TL; and e) generating a first output signal (OSI-OSP) for all neurons having a potential value exceeding a second threshold TF, and a second output signal, different from the first one, for all other neurons. A digital electronic circuit and system configured for carrying out such a method.

Abstract: A method of performing unsupervised detection of repeating patterns in a series of events, includes a) Providing a plurality of neurons, each neuron being representative of W event types; b) Acquiring an input packet comprising N successive events of the series; c) Attributing to at least some neurons a potential value, representative of the number of common events between the input packet and the neuron; d) Modify the event types of neurons having a potential value exceeding a first threshold TL; and e) generating a first output signal for all neurons having a potential value exceeding a second threshold TF, and a second output signal, different from the first one, for all other neurons. A digital electronic circuit and system configured for carrying out such a method is also provided.