US 11,755,891 B2
Devices and methods for increasing the speed or power efficiency of a computer when performing machine learning using spiking neural networks
Craig Michael Vineyard, Cedar Crest, NM (US); William Mark Severa, Albuquerque, NM (US); James Bradley Aimone, Albuquerque, NM (US); and Stephen Joseph Verzi, Albuquerque, NM (US)
Assigned to National Technology & Engineering Solutions of Sandia, LLC, Albuquerque, NM (US)
Filed by National Technology & Engineering Solutions of Sandia, LLC, Albuquerque, NM (US)
Filed on Jun. 20, 2018, as Appl. No. 16/13,810.
Prior Publication US 2019/0392301 A1, Dec. 26, 2019
Int. Cl. G06N 3/08 (2006.01); G06K 9/62 (2022.01); G06N 20/00 (2019.01)
CPC G06N 3/08 (2013.01) [G06K 9/6269 (2013.01); G06K 9/6276 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for increasing a speed and efficiency of a computer when performing machine learning using spiking neural networks, the method comprising computer-implemented operations of:
receiving, in a spiking neural network, a plurality of input values upon which a machine learning algorithm is based;
correlating, for each input value, a corresponding response speed of a corresponding neuron to a corresponding equivalence relationship between the input value to a corresponding latency of the corresponding neuron, wherein neurons that trigger faster than other neurons represent close relationships between input values and neuron latencies, wherein latencies of the neurons represent data points used in performing the machine learning, and wherein a plurality of equivalence relationships are formed as a result of correlating; and
performing the machine learning using the plurality of equivalence relationships.