Neural network training based on FPGA with floating point number format and it's performance

Neural Computing and Applications

Volumn 20, Issue 2, 2011, Pages 195-202

  Çavuşlu, Mehmet Ali ^a   Karakuzu, Cihan ^b   Şahin, Suhap ^b   Yakut, Mehmet ^b  

^a Y Vizyon Sinyalizasyon Tic Ltd ti   (Turkey)

^b KOCAELI UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Floating point arithmetic; FPGA; Parallel programming; VHDL

Indexed keywords

BACKPROPAGATION; COMPUTER HARDWARE DESCRIPTION LANGUAGES; DATA HANDLING; DIGITAL ARITHMETIC; FEEDFORWARD NEURAL NETWORKS; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); NEURAL NETWORKS; PARALLEL PROGRAMMING;

ANN TRAININGS; BIT LENGTHS; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; FLOATING POINT NUMBERS; FPGA(FIELD PROGRAMMABLE GATE ARRAY); NEURAL NETWORK TRAINING; PARALLEL DATA PROCESSING; XILINX FPGA;

MULTILAYER NEURAL NETWORKS;

EID: 79951768625     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-010-0423-3     Document Type: Article

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