OPERATION METHOD FOR ARTIFICIAL NEURAL NETWORK

An operation method of an artificial neural network is provided. The operation method includes: dividing input information into a plurality of sub-input information, and expanding kernel information to generate expanded kernel information; performing a Fast Fourier Transform (FFT) on the sub-input i...

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Bibliographic Details
Main Authors Wang, Wei-Chen, Ho, Chien-Chung, Ho, Shu-Yin, Chang, Yuan-Hao
Format Patent
LanguageEnglish
Published 27.05.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:An operation method of an artificial neural network is provided. The operation method includes: dividing input information into a plurality of sub-input information, and expanding kernel information to generate expanded kernel information; performing a Fast Fourier Transform (FFT) on the sub-input information and the expanded kernel information to respectively generate a plurality of frequency domain sub-input information and frequency domain expanded kernel information; respectively performing a multiplying operation on the frequency domain expanded kernel information and the frequency domain sub-input information to respectively generate a plurality of sub-feature maps; and performing an inverse FFT on the sub-feature maps to provide a plurality of converted sub-feature maps for executing a feature extraction operation of the artificial neural network.
Bibliography:Application Number: US202017096575