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1. (WO2013119867) METHODS AND APPARATUS FOR SPIKING NEURAL COMPUTATION

Pub. No.:    WO/2013/119867    International Application No.:    PCT/US2013/025219
Publication Date: Fri Aug 16 01:59:59 CEST 2013 International Filing Date: Fri Feb 08 00:59:59 CET 2013
IPC: G06N 3/04
G06N 3/08
Applicants: QUALCOMM INCORPORATED
Inventors: HUNZINGER, Jason Frank
APARIN, Vladimir
Title: METHODS AND APPARATUS FOR SPIKING NEURAL COMPUTATION
Abstract:
Certain aspects of the present disclosure provide methods and apparatus for spiking neural computation of general linear systems. One example aspect is a neuron model that codes information in the relative timing between spikes. However, synaptic weights are unnecessary. In other words, a connection may either exist (significant synapse) or not (insignificant or non-existent synapse). Certain aspects of the present disclosure use binary-valued inputs and outputs and do not require post-synaptic filtering. However, certain aspects may involve modeling of connection delays (e.g., dendritic delays). A single neuron model may be used to compute any general linear transformation x = AX + BU to any arbitrary precision. This neuron model may also be capable of learning, such as learning input delays (e.g., corresponding to scaling values) to achieve a target output delay (or output value). Learning may also be used to determine a logical relation of causal inputs.