2021 BRN Discussion, page-1768

This is another Akida SCNN patent application, not sure if it's been posted before;

https://worldwide.espacenet.com/patent/search/family/074189798/publication/WO2021016544A1?q=brainchip

WO2021016544A1 EVENT-BASED CLASSIFICATION OF FEATURES IN A RECONFIGURABLE AND TEMPORALLY CODED CONVOLUTIONAL SPIKING NEURAL NETWORK

Priorities US201962878426P·2019-07-25

Application US2020043456W·2020-07-24

Publication WO2021016544A1·2021-01-28

Published as CN112308107A;US2021027152A1;WO2021016544A1

Embodiments of the present invention provides a system and method of learning and classifying features to identify objects in images using a temporally coded deep spiking neural network, a classifying method by using a reconfigurable spiking neural network device or software comprising configuration logic, a plurality of reconfigurable spiking neurons and a second plurality of synapses.

The spiking neural network device or software further comprises a plurality of user-selectable convolution and pooling engines.

Each fully connected and convolution engine is capable of learning features, thus producing a plurality of feature map layerscorresponding to a plurality of regions respectively, each of the convolution engines being used for obtaining a response of a neuron in the corresponding region.

The neurons are modeled as Integrate and Fire neurons with a non-linear time constant, forming individual integrating threshold units with a spike output, eliminating the need for multiplication and addition of floating-point numbers.

Just when I thought I was getting my head around SNNs.