Invention Application
- 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.: US20210073650A1Publication Date: 2021-03-11
- Inventor: Matthias REISSER , Saurabh Kedar PITRE , Xiaochun ZHU , Edward Harris 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
- Main IPC: G06N3/10
- IPC: G06N3/10 ; G06N3/04 ; G06F17/16

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
- US11790241B2 Systems and methods for modifying neural networks for binary processing applications Public/Granted day:2023-10-17
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