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158
Analysis of LDPC convolutional codes derived from LDPC block codes 2008.pdf
Analysis of LDPC convolutional codes derived from LDPC block codes 2008Analysis of LDPC convolutional codes derived from LDPC block codes 2008Analysis of LDPC convolutional codes derived from LDPC block codes 2008
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155
New Frontiers in Polar Coding Large Kernels, Convolutional Decoding, and Deletion Channels.pdf
CALIFORNIA,SAN DIEGONew Frontiers PolarCoding:Large Kernels, Convolutional Decoding, DeletionChannel
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126
Exploring the Design Space of Deep Convolutional Neural Networks at Large Scale(大规模探索深度卷积神经网络的设计空间).pdf
DesignSpace ofDeep Convolutional Neural Networks LargeScalebyForrest IandolaA dissertation submitted
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231
Summary of References Related to Convolutional Neural Networks.pdf
ReferencesRelated toConvolutional Neural NetworksMiquel Perello, E-mail: miquel.perellonieto@aalto.f
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174
convolutional models for landmine identification with ground penetrating radar tu delft institutional repository.pdf
ConvolutionalModels LandmineIdentification GroundPenetrating Radar Convolutional Models LandmineIden
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133
An Analytical Packet Error Rate Prediction for Punctured Convolutional Codes and an Application to.pdf
An Analytical Packet Error Rate Prediction for Punctured Convolutional Codes and an Application to
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233
Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata.pdf
Improving Biological Object Classification in Plankton Images Using Convolutional Neural Networks, Geometric Features, and Context Metadata
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105
performance of coherent and noncoherent rake receivers with convolutional coding ricean fading and pulse-noise interference(379.21kb).pdf
performance of coherent and noncoherent rake receivers with convolutional coding ricean fading and pulse-noise interference(379.21kb)
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120
Cost-Efficient Approximate Log Multipliers for Convolutional Neural Networks(卷积神经网络的经济高效的近似对数乘法器).pdf
Cost-Efficient Approximate Log Multipliers for Convolutional Neural Networks（卷积神经网络的经济高效的近似对数乘法器）
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