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Design and Implementation of Signal Processing Systems

STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS


Machine-learning algorithms are being employed in an increasing range of applications, spanning high-performance and energy-constrained platforms. It has been noted that the statistical nature of the algorithms can open up new opportunities for throughput and energy efficiency, by moving hardware into design regimes not limited to deterministic models of computation. This work aims to enable high accuracy in machine-learning inference systems, where computations are substantially affected by hardware variability.

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Authors:
Bonan Zhang, Lung-Yen Chen, Naveen Verma
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10 May 2019 - 12:07am
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[1] Bonan Zhang, Lung-Yen Chen, Naveen Verma, "STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4265. Accessed: Aug. 19, 2019.
@article{4265-19,
url = {http://sigport.org/4265},
author = {Bonan Zhang; Lung-Yen Chen; Naveen Verma },
publisher = {IEEE SigPort},
title = {STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS},
year = {2019} }
TY - EJOUR
T1 - STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS
AU - Bonan Zhang; Lung-Yen Chen; Naveen Verma
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4265
ER -
Bonan Zhang, Lung-Yen Chen, Naveen Verma. (2019). STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS. IEEE SigPort. http://sigport.org/4265
Bonan Zhang, Lung-Yen Chen, Naveen Verma, 2019. STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS. Available at: http://sigport.org/4265.
Bonan Zhang, Lung-Yen Chen, Naveen Verma. (2019). "STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS." Web.
1. Bonan Zhang, Lung-Yen Chen, Naveen Verma. STOCHASTIC DATA-DRIVEN HARDWARE RESILIENCE TO EFFICIENTLY TRAIN INFERENCE MODELS FOR STOCHASTIC HARDWARE IMPLEMENTATIONS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4265

SVM-based Seal Imprint Verification Using Edge Difference

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9 May 2019 - 9:29pm
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[1] , "SVM-based Seal Imprint Verification Using Edge Difference", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4250. Accessed: Aug. 19, 2019.
@article{4250-19,
url = {http://sigport.org/4250},
author = { },
publisher = {IEEE SigPort},
title = {SVM-based Seal Imprint Verification Using Edge Difference},
year = {2019} }
TY - EJOUR
T1 - SVM-based Seal Imprint Verification Using Edge Difference
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4250
ER -
. (2019). SVM-based Seal Imprint Verification Using Edge Difference. IEEE SigPort. http://sigport.org/4250
, 2019. SVM-based Seal Imprint Verification Using Edge Difference. Available at: http://sigport.org/4250.
. (2019). "SVM-based Seal Imprint Verification Using Edge Difference." Web.
1. . SVM-based Seal Imprint Verification Using Edge Difference [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4250

ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS

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Authors:
Joao Gante, Gabriel Falcao, Leonel Sousa
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8 May 2019 - 2:55pm
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[1] Joao Gante, Gabriel Falcao, Leonel Sousa, "ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4130. Accessed: Aug. 19, 2019.
@article{4130-19,
url = {http://sigport.org/4130},
author = {Joao Gante; Gabriel Falcao; Leonel Sousa },
publisher = {IEEE SigPort},
title = {ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS},
year = {2019} }
TY - EJOUR
T1 - ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS
AU - Joao Gante; Gabriel Falcao; Leonel Sousa
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4130
ER -
Joao Gante, Gabriel Falcao, Leonel Sousa. (2019). ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS. IEEE SigPort. http://sigport.org/4130
Joao Gante, Gabriel Falcao, Leonel Sousa, 2019. ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS. Available at: http://sigport.org/4130.
Joao Gante, Gabriel Falcao, Leonel Sousa. (2019). "ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS." Web.
1. Joao Gante, Gabriel Falcao, Leonel Sousa. ENHANCING BEAMFORMED FINGERPRINT OUTDOOR POSITIONING WITH HIERARCHICAL CONVOLUTIONAL NEURAL NETWORKS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4130

Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction


Deep learning models have been shown to be capable of extracting high-level representations from the increasing amount of customer-level data generated via fast-growing financial activities. In financial data, dynamic features that evolve with time are commonly observed. However, such time dependencies are often ignored in classical classification models. In this study, we propose to learn a Recurrent Neural Network (RNN) feature extractor with GRU on credit card payment history to leverage the time dependencies embedded in these dynamic features.

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Authors:
Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin
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8 May 2019 - 9:27am
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[1] Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin, "Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4093. Accessed: Aug. 19, 2019.
@article{4093-19,
url = {http://sigport.org/4093},
author = {Te-Cheng Hsu; Shing-Tzuo Liou; Yun-Ping Wang; Yung-Shun Huang; Che Lin },
publisher = {IEEE SigPort},
title = {Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction},
year = {2019} }
TY - EJOUR
T1 - Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction
AU - Te-Cheng Hsu; Shing-Tzuo Liou; Yun-Ping Wang; Yung-Shun Huang; Che Lin
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4093
ER -
Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin. (2019). Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction. IEEE SigPort. http://sigport.org/4093
Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin, 2019. Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction. Available at: http://sigport.org/4093.
Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin. (2019). "Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction." Web.
1. Te-Cheng Hsu, Shing-Tzuo Liou, Yun-Ping Wang, Yung-Shun Huang, Che Lin. Enhanced Recurrent Neural Network for Combining Static and Dynamic Features for Credit Card Default Prediction [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4093

GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES


Belief Propagation (BP) decoding provides soft outputs and features high-level parallelism. In this paper, we propose an optimized software BP decoder for polar codes on graphics processing units (GPUs). A full-parallel decoding architecture for codes with length n ≤ 2048 is presented to simultaneously update n/2 processing elements (PEs) within each stage and achieve high on-chip memory utilization by using

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Authors:
Zhanxian Liu, Rongke Liu, Zhiyuan Yan, Ling Zhao
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8 May 2019 - 1:19am
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[1] Zhanxian Liu, Rongke Liu, Zhiyuan Yan, Ling Zhao, "GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4008. Accessed: Aug. 19, 2019.
@article{4008-19,
url = {http://sigport.org/4008},
author = {Zhanxian Liu; Rongke Liu; Zhiyuan Yan; Ling Zhao },
publisher = {IEEE SigPort},
title = {GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES},
year = {2019} }
TY - EJOUR
T1 - GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES
AU - Zhanxian Liu; Rongke Liu; Zhiyuan Yan; Ling Zhao
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4008
ER -
Zhanxian Liu, Rongke Liu, Zhiyuan Yan, Ling Zhao. (2019). GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES. IEEE SigPort. http://sigport.org/4008
Zhanxian Liu, Rongke Liu, Zhiyuan Yan, Ling Zhao, 2019. GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES. Available at: http://sigport.org/4008.
Zhanxian Liu, Rongke Liu, Zhiyuan Yan, Ling Zhao. (2019). "GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES." Web.
1. Zhanxian Liu, Rongke Liu, Zhiyuan Yan, Ling Zhao. GPU-BASED IMPLEMENTATION OF BELIEF PROPAGATION DECODING FOR POLAR CODES [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4008

ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)

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Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps
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7 May 2019 - 6:58pm
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[1] Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps, "ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3966. Accessed: Aug. 19, 2019.
@article{3966-19,
url = {http://sigport.org/3966},
author = {Tharshini Gunendradasan; Saad Irtza; Eliathamby Ambikairajah; Julien Epps },
publisher = {IEEE SigPort},
title = {ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)},
year = {2019} }
TY - EJOUR
T1 - ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)
AU - Tharshini Gunendradasan; Saad Irtza; Eliathamby Ambikairajah; Julien Epps
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3966
ER -
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps. (2019). ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION). IEEE SigPort. http://sigport.org/3966
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps, 2019. ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION). Available at: http://sigport.org/3966.
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps. (2019). "ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)." Web.
1. Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps. ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION) [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3966

ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)

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Authors:
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps
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7 May 2019 - 6:58pm
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[1] Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps, "ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3965. Accessed: Aug. 19, 2019.
@article{3965-19,
url = {http://sigport.org/3965},
author = {Tharshini Gunendradasan; Saad Irtza; Eliathamby Ambikairajah; Julien Epps },
publisher = {IEEE SigPort},
title = {ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)},
year = {2019} }
TY - EJOUR
T1 - ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)
AU - Tharshini Gunendradasan; Saad Irtza; Eliathamby Ambikairajah; Julien Epps
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3965
ER -
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps. (2019). ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION). IEEE SigPort. http://sigport.org/3965
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps, 2019. ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION). Available at: http://sigport.org/3965.
Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps. (2019). "ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION)." Web.
1. Tharshini Gunendradasan, Saad Irtza, Eliathamby Ambikairajah, Julien Epps. ICASSP 2019 Poster (TRANSMISSION LINE COCHLEAR MODEL BASED AM-FM FEATURES FOR REPLAY ATTACK DETECTION) [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3965

Adaptive Multi-Trace Carving Based on Dynamic Programming


In this work, we study the problem of tracking multiple frequency components in a noisy signal using a spectrogram-based method. Previous approaches such as image processing based or hidden Markov model-based methods may not be capable of tracking multiple frequency components, may require extensive training, and may be time-consuming. To address these issues, we propose an accurate and efficient method named Adaptive Multi-Trace Carving (AMTC) for tracking multiple frequency traces by iterative forward and backward dynamic programming and adaptive trace compensation.

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Authors:
Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu
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7 March 2019 - 10:50am
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[PDF] AMTC Asilomar 2018 poster

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[1] Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu, "Adaptive Multi-Trace Carving Based on Dynamic Programming", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3845. Accessed: Aug. 19, 2019.
@article{3845-19,
url = {http://sigport.org/3845},
author = {Qiang Zhu; Mingliang Chen; Chau-Wai Wong; Min Wu },
publisher = {IEEE SigPort},
title = {Adaptive Multi-Trace Carving Based on Dynamic Programming},
year = {2019} }
TY - EJOUR
T1 - Adaptive Multi-Trace Carving Based on Dynamic Programming
AU - Qiang Zhu; Mingliang Chen; Chau-Wai Wong; Min Wu
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3845
ER -
Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu. (2019). Adaptive Multi-Trace Carving Based on Dynamic Programming. IEEE SigPort. http://sigport.org/3845
Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu, 2019. Adaptive Multi-Trace Carving Based on Dynamic Programming. Available at: http://sigport.org/3845.
Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu. (2019). "Adaptive Multi-Trace Carving Based on Dynamic Programming." Web.
1. Qiang Zhu, Mingliang Chen, Chau-Wai Wong, Min Wu. Adaptive Multi-Trace Carving Based on Dynamic Programming [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3845

JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH


Compared with traditional device-to-device (D2D) communication networks, the users in the cache-enabled D2D communication networks can easily obtain their requested contentsfromthenearbyusers,andreducethebackhaulcosts. In this paper, we investigate the caching strategy for the cacheenabled D2D communication networks, with the consideration of caching placement and caching delivery. The content popularity and user mobility are predicted by a machine learning approach of echo state networks (ESNs) in order to determine which content to cache and where to cache.

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Authors:
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han
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27 March 2019 - 9:05am
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[1] Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han, "JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3715. Accessed: Aug. 19, 2019.
@article{3715-18,
url = {http://sigport.org/3715},
author = {Jiaying Yin; Lixin Li; Yang Xu; Wei Liang; Huisheng Zhang; and Zhu Han },
publisher = {IEEE SigPort},
title = {JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH},
year = {2018} }
TY - EJOUR
T1 - JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH
AU - Jiaying Yin; Lixin Li; Yang Xu; Wei Liang; Huisheng Zhang; and Zhu Han
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3715
ER -
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han. (2018). JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH. IEEE SigPort. http://sigport.org/3715
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han, 2018. JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH. Available at: http://sigport.org/3715.
Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han. (2018). "JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH." Web.
1. Jiaying Yin, Lixin Li, Yang Xu, Wei Liang, Huisheng Zhang, and Zhu Han. JOINT CONTENT POPULARITY PREDICTION AND CONTENT DELIVERY POLICY FOR CACHE-ENABLED D2D NETWORKS: A DEEP REINFORCEMENT LEARNING APPROACH [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3715

APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES

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17 April 2018 - 9:07pm
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[1] , "APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2957. Accessed: Aug. 19, 2019.
@article{2957-18,
url = {http://sigport.org/2957},
author = { },
publisher = {IEEE SigPort},
title = {APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES},
year = {2018} }
TY - EJOUR
T1 - APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2957
ER -
. (2018). APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES. IEEE SigPort. http://sigport.org/2957
, 2018. APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES. Available at: http://sigport.org/2957.
. (2018). "APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES." Web.
1. . APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2957

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