US 11,989,645 B2
Event-based extraction of features in a convolutional spiking neural network
Douglas McLelland, Gers (FR); Kristofor D. Carlson, Willoughby Hills, OH (US); Harshil K. Patel, Darch (AU); Anup A. Vanarse, Darch (AU); and Milind Joshi, Edgewater (AU)
Assigned to BrainChip, Inc., Laguna Hills, CA (US)
Filed by BrainChip, Inc., Laguna Hills, CA (US)
Filed on Jan. 25, 2022, as Appl. No. 17/583,640.
Application 17/583,640 is a continuation in part of application No. PCT/US2020/043456, filed on Jul. 24, 2020.
Claims priority of provisional application 62/878,426, filed on Jul. 25, 2019.
Prior Publication US 2022/0147797 A1, May 12, 2022
Int. Cl. G06N 3/063 (2023.01); G06N 3/049 (2023.01); G06N 3/08 (2023.01); G06T 3/40 (2006.01); G06T 3/4046 (2024.01); G11C 11/41 (2006.01); G11C 11/54 (2006.01)
CPC G06N 3/063 (2013.01) [G06N 3/049 (2013.01); G06N 3/08 (2013.01); G06T 3/4046 (2013.01); G11C 11/41 (2013.01); G11C 11/54 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A system, comprising:
a memory for storing data representative of at least one kernel;
a plurality of spiking neuron circuits;
an input module for receiving spikes related to digital data, wherein each spike is relevant to a spiking neuron circuit and each spike has an associated spatial coordinate corresponding to a location in an input spike array;
a transformation module configured to:
transform the kernel to produce a transformed kernel having an increased resolution relative to the kernel; and/or
transform the input spike array to produce a transformed input spike array having an increased resolution relative to the input spike array;
a packet collection module configured to collect spikes until a predetermined number of spikes relevant to the input spike array have been collected in a packet in memory, and to organize the collected relevant spikes in the packet based on the associated spatial coordinates of the collected relevant spikes; and
a convolutional neural processor configured to perform an event-based convolution using the memory and at least one of the transformed input spike array and the transformed kernel.