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项目作者:
yoloh3
项目描述 :
Artificial neural network project for LSI Design Contest 2018, Japan
高级语言:
Verilog
项目主页:
项目地址:
git://github.com/yoloh3/Ann.git
创建时间:
2017-10-03T09:44:54Z
项目社区:
https://github.com/yoloh3/Ann
开源协议:
下载
SLIDE-SISLAB_team_2018_1648046484238.pptx
Backwork_1648046492129.pptx
Hunghh_59d - Intro 2 Backpropagation - 4_11_2017_1648046492323.pptx
Hunghh_59d - Intro Backpropagation_1648046492697.pptx
Hunghh_59d - Weekly progress - 18_11_2017_1648046493040.pptx
LSI-Design-Constet-2018-Gradient Descent_ Thuat Nguyen_1648046493346.pptx
LSI-Design-Contest-2018_Gradient descent variants_1648046493742.pptx
LSI-Design-Contest-2018_Neural Network and hardware design_Xuan-Thuan Nguyen_1648046494608.pptx
comparion_version_1648046498947.pptx
Mang_no_ron_nhan_tao_1648046497316.doc
Proposal document - Hardware implementation an artifical neuron network using backpropapgation algorithm_1648046497626.docx
PAPER-SISLAB_team_2018_1648046483938.pdf
Shoushan2010 - A Single Layer Architecture t oFPGA Implementation of BP Artificial Neural Network_1648046484864.pdf
biradar2015 - FPGA Implementation of a Multilayer Artificial _1648046485070.pdf
gomperts2011 - Development and Implementation of Parameterized_1648046485223.pdf
hunter2012 - Selection of Proper Neural Network Sizes and_1648046485484.pdf
napoli2014 - Reduced Complexity Digital Back-Propagation_1648046485993.pdf
ortegazamorano2014 - FPGA Implementation of the C-Mantec Neural_1648046486203.pdf
rowley1998 - Neural Network-Based Face Detection_1648046486602.pdf
Ardakani2017 - VLSI Implementation of Deep Neural Network_1648046487173.pdf
Energy-Efficiency and Accuracy of Stochastic_1648046487454.pdf
Huang2016dnw - Deep Networks with Stochastic Dept_1648046487863.pdf
Li2016usc - Using Stochastic Computing to Reduce the Hardware_1648046488021.pdf
Ting2017eah - Eliminating a Hidden Error S_1648046488251.pdf
Xie2017 - Fully-Parallel Area-Efficient Deep Neural Net-work Design using Stochastic Computing_1648046488564.pdf
alaghi2014faa - Fast and Accurate Stochastic Circuits_1648046488692.pdf
brown2001snc - Stochastic Neural Computation_1648046489047.pdf
jlpea-07-00029_1648046489233.pdf
lee2017 - Energy-Efficient hybrid Stochasti-Binary Neural Networks for Near-Sensor Computing_1648046489473.pdf
li2015 - An FPGA Implementation of a Restricted Boltzmann_1648046489719.pdf
liu2016 - Computing Hyperbolic Tangent and Sigmoid_1648046489843.pdf
moons2014 - Energy-Efficiency and Accuracy of Stochastic_1648046490091.pdf
ren2017shd - SC-DCNN Highly-Scalable Deep Convolutional_1648046490462.pdf
sim2017 - A New Stochastic Computing Multiplier with Application to Deep_1648046491023.pdf
sim2017sca - Scalable Stochastic-Computing Accelerator for Convolutional Neural Networks_1648046491375.pdf
yeo2016 - Stochastic Implementation of the Activation Function _1648046491429.pdf
yuan2016 - High-Accuracy FIR Filter Design using Stochastic Computing_1648046491532.pdf
tisan2016 - An End User Platform for FPGA-based Design _1648046491704.pdf
zamanlooy2014 - Efficient VLSI Implementation of Neural Networks_1648046491935.pdf
2012-1158-160208231021_1648046494848.pdf
Fixed point package user's guide_1648046495475.pdf
Lsi-contest.com - Hardware implementation outline_1648046496818.pdf
Lsi-contest.com - Level 2_1648046496989.pdf
Lsi-contest.com - Neural Network and optimization of calculation_1648046497072.pdf
Neural Network and optimization of calculation_1648046497463.pdf
Using neural nets to recognize handwritten digits_1648046497770.pdf
mlp2-151222090756_1648046498061.pdf