Application of the residue number system to reduce hardware costs of the convolutional neural network implementation

Convolutional neural networks are a promising tool for solving the problem of pattern recognition. Most well-known convolutional neural networks implementations require a significant amount of memory to store weights in the process of learning and working. We propose a convolutional neural network a...

Celý popis

Podrobná bibliografie

Vydáno v:	Mathematics and computers in simulation Ročník 177; s. 232 - 243
Hlavní autoři:	Valueva, M.V., Nagornov, N.N., Lyakhov, P.A., Valuev, G.V., Chervyakov, N.I.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.11.2020
Témata:	Convolutional neural networks Field-programmable gate array (FPGA) Image processing Quantization noise Residue number system Quantization noise Residue number system Image processing Field-programmable gate array (FPGA) Convolutional neural networks
ISSN:	0378-4754, 1872-7166
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!