Invention Grant
- Patent Title: Systems and methods for modifying neural networks for binary processing applications
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Application No.: US17016130Application Date: 2020-09-09
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Publication No.: US11790241B2Publication Date: 2023-10-17
- Inventor: Matthias Reisser , Saurabh Kedar Pitre , Xiaochun Zhu , Edward Harrison Teague , Zhongze Wang , Max Welling
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agency: Patterson + Sheridan LLP
- Main IPC: G06F17/16
- IPC: G06F17/16 ; G06N3/10 ; G06N3/047

Abstract:
In one embodiment, a method of simulating an operation of an artificial neural network on a binary neural network processor includes receiving a binary input vector for a layer including a probabilistic binary weight matrix and performing vector-matrix multiplication of the input vector with the probabilistic binary weight matrix, wherein the multiplication results are modified by simulated binary-neural-processing hardware noise, to generate a binary output vector, where the simulation is performed in the forward pass of a training algorithm for a neural network model for the binary-neural-processing hardware.
Public/Granted literature
- US20210073650A1 SYSTEMS AND METHODS FOR MODIFYING NEURAL NETWORKS FOR BINARY PROCESSING APPLICATIONS Public/Granted day:2021-03-11
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