2022 BRN Discussion, page-116

https://globaldossier.uspto.gov/#/details/US/16938254/A/118916


The next patent will be issued on the 18/1/2022

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https://patents.google.com/patent/US20210027152A1/en

Event-based classification of features in a reconfigurable and temporally coded convolutional spiking neural network

Abstract
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 layers corresponding 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.