The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 29, 2025
Filed:
Aug. 07, 2019
Shanghai Ic R&d Center Co., Ltd., Shanghai, CN;
Ling Shen, Shanghai, CN;
Yu Jiang, Shanghai, CN;
Huijie Yan, Shanghai, CN;
Zhifang Li, Shanghai, CN;
Jianxin Wen, Shanghai, CN;
SHANGHAI IC R&D CENTER CO., LTD., Shanghai, CN;
SHANGHAI INTEGRATED CIRCUIT EQUIPMENT & MATERIALS INDUSTRY INNOVATION CENTER CO., LTD, Shanghai, CN;
Abstract
A single-layered linear neural network based on a cell synapse structure comprising a pre-synapse and a post-synapse, the pre-synapse comprises a plurality of precursor resistors, number of the precursor resistors is m, one end of the precursor resistors in the pre-synapse is jointly connected with an intermediate point, and another end of the precursor resistors is respectively connected with each of a plurality of precursor signal input ends, number of the precursor signal input ends is m; the precursor signal input ends are used for receiving input voltages; the post-synapse comprises a plurality of posterior resistors, number of the precursor resistors is n, one end of the posterior resistors in the post-synapse is jointly connected with the intermediate point, and another end of the posterior resistors is respectively connected with each of a plurality of posterior signal output ends, number of the posterior signal output ends is n; the posterior signal output ends are used for outputting currents. The invention provides a single-layered linear neural network based on cell synapse structure, which can reduce the number of resistors; in addition, a weight between an external precursor neuron and an external posterior neuron can be changed only by adjusting two variable resistors or one of the two variable resistors.