Invention Grant
- Patent Title: Apparatus and method for executing reversal training of artificial neural network
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Application No.: US16038872Application Date: 2018-07-18
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Publication No.: US10713567B2Publication Date: 2020-07-14
- Inventor: Shaoli Liu , Qi Guo , Yunji Chen , Tianshi Chen
- Applicant: CAMBRICON TECHNOLOGIES CORPORATION LIMITED
- Applicant Address: CN Beijing
- Assignee: CAMBRICON TECHNOLOGIES CORPORATION LIMITED
- Current Assignee: CAMBRICON TECHNOLOGIES CORPORATION LIMITED
- Current Assignee Address: CN Beijing
- Agency: Getech Law LLC
- Agent Jun Ye
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@5a56d5a1
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F9/22 ; G06F9/30 ; G06F9/38 ; G06F13/28 ; G06F15/173 ; G06N3/04

Abstract:
An apparatus for executing backpropagation of an artificial neural network comprises an instruction caching unit, a controller unit, a direct memory access unit, an interconnection unit, a master computation module, and multiple slave computation modules. For each layer in a multilayer neural network, weighted summation may be performed on input gradient vectors to calculate an output gradient vector of this layer. The output gradient vector may be multiplied by a derivative value of a next-layer activation function on which forward operation is performed, so that a next-layer input gradient vector can be obtained. The input gradient vector may be multiplied by an input neuron counterpoint in forward operation to obtain the gradient of a weight value of this layer, and the weight value of this layer can be updated according to the gradient of the obtained weight value of this layer.
Public/Granted literature
- US20180322392A1 APPARATUS AND METHOD FOR EXECUTING REVERSAL TRAINING OF ARTIFICIAL NEURAL NETWORK Public/Granted day:2018-11-08
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