http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115222026-A

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Predicate Object
assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ea26a2c4131139229dbc30c78c4e53c4
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-063
filingDate 2021-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_3a4a51152aa74dcdafd6b34d9630f32a
publicationDate 2022-10-21-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-115222026-A
titleOfInvention A kind of spiking neural network hardware circuit
abstract An impulse neural network hardware circuit includes an electronic synapse module, a pre-neuron module, a post-neuron module, a power supply module, and a microprocessor. Each pre-neuron in the pre-neuron module sequentially generates pre-pulses entering the electronic synapse module according to the one-dimensional time series input by the microprocessor. The pre-pulse entering the post-neuron module through the electronic synaptic module will be integrated by the post-neuron module and continuously promote the decrease of the resistance value of the low-doped memristor until the post-neuron generates spikes and post-pulses. The post-pulse will quickly propagate to the electronic synapse module to integrate with the pre-pulse, and adjust the resistance value of a specific electronic synapse based on the time-dependent synaptic plasticity learning rules (that is, modify the synaptic weight); the microprocessor will Record the time of the earliest spike and the post-neuron sequence, and use this to mark the learning information. After learning all the information, the system can classify different information according to the order and time in the training result.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116306857-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116316503-A
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http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115545190-A
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priorityDate 2021-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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Total number of triples: 23.