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Design and Implementation of Signal Processing Systems

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: Apr. 18, 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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GlobalSIP_YJY.pdf

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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: Apr. 18, 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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icassp2018_poster.pdf

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[1] , "APPROXIMATE BELIEF PROPAGATION DECODER FOR POLAR CODES", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2957. Accessed: Apr. 18, 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

Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining

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15 April 2018 - 10:13am
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ICASSP Paper #2491 Slides.pdf

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[1] , "Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2896. Accessed: Apr. 18, 2019.
@article{2896-18,
url = {http://sigport.org/2896},
author = { },
publisher = {IEEE SigPort},
title = {Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining},
year = {2018} }
TY - EJOUR
T1 - Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2896
ER -
. (2018). Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining. IEEE SigPort. http://sigport.org/2896
, 2018. Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining. Available at: http://sigport.org/2896.
. (2018). "Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining." Web.
1. . Efficient Deep Convolutional Neural Networks Accelerator without Multiplication and Retraining [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2896

ICASSP-2018-IOT-L1.4


The emerging compressed sensing (CS) technique enables new reduced-complexity designs of sensor nodes and helps to save overall transmission power in wireless sensor network. Because of the linearity of its encoding process, CS is vulnerable to Ciphertext-Only Attack (COA) and Known-Plaintext Attack (KPA). The prior works use multiple sensing matrices as the shared secret key, however, the complexity overhead of front-end sensor and synchronization issue arising from multiple keys should be well considered.

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13 April 2018 - 7:14pm
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ICASSP'18_lecture_v5_up.pdf

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[1] , "ICASSP-2018-IOT-L1.4", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2772. Accessed: Apr. 18, 2019.
@article{2772-18,
url = {http://sigport.org/2772},
author = { },
publisher = {IEEE SigPort},
title = {ICASSP-2018-IOT-L1.4},
year = {2018} }
TY - EJOUR
T1 - ICASSP-2018-IOT-L1.4
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2772
ER -
. (2018). ICASSP-2018-IOT-L1.4. IEEE SigPort. http://sigport.org/2772
, 2018. ICASSP-2018-IOT-L1.4. Available at: http://sigport.org/2772.
. (2018). "ICASSP-2018-IOT-L1.4." Web.
1. . ICASSP-2018-IOT-L1.4 [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2772

Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting


This paper considers a two-user multiple-input single-output Gaussian broadcast channel model with two sorts of information transfer, i.e., multicasting and confidential broadcasting. Specifically, three service messages are combined at the transmitter. The transmitter sends a
multicast message to both users, and a confidential message to each user which is kept perfectly secret from the other user. Our goal

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13 November 2017 - 9:38pm
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GS17_Slides.pptx

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[1] , "Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2346. Accessed: Apr. 18, 2019.
@article{2346-17,
url = {http://sigport.org/2346},
author = { },
publisher = {IEEE SigPort},
title = {Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting},
year = {2017} }
TY - EJOUR
T1 - Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2346
ER -
. (2017). Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting. IEEE SigPort. http://sigport.org/2346
, 2017. Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting. Available at: http://sigport.org/2346.
. (2017). "Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting." Web.
1. . Transmitter Optimization for MISO System with Service Integration of Multicasting and Confidential Broadcasting [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2346

A Mobile EEG System for Practical Applications


In this study, we present a new 64-channel mobile EEG system (NeusenW, Neuracle Inc.), and compare it to a state-of-the-art wired laboratory EEG system and evaluate the EEG signal quality. Previous studies were only performed on seated participants in laboratory environments, and only a very limited number focus on motion conditions. In this study, we instead implemented experiments in standing, walking and running conditions.

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Authors:
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao
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13 November 2017 - 4:08pm
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poster_SIP_rami3.pdf

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[1] Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao, "A Mobile EEG System for Practical Applications", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2341. Accessed: Apr. 18, 2019.
@article{2341-17,
url = {http://sigport.org/2341},
author = {Xiaoshan Huang; Erwei Yin; Yijun Wang; Rami Saab; Xiaorong Gao },
publisher = {IEEE SigPort},
title = {A Mobile EEG System for Practical Applications},
year = {2017} }
TY - EJOUR
T1 - A Mobile EEG System for Practical Applications
AU - Xiaoshan Huang; Erwei Yin; Yijun Wang; Rami Saab; Xiaorong Gao
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2341
ER -
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. (2017). A Mobile EEG System for Practical Applications. IEEE SigPort. http://sigport.org/2341
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao, 2017. A Mobile EEG System for Practical Applications. Available at: http://sigport.org/2341.
Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. (2017). "A Mobile EEG System for Practical Applications." Web.
1. Xiaoshan Huang, Erwei Yin, Yijun Wang, Rami Saab, Xiaorong Gao. A Mobile EEG System for Practical Applications [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2341

Block-wise Lensless Compressive Camera


The existing lensless compressive camera (L2C2) [1] suffers from low capture rates, resulting in low resolution images when acquired over a short time. In this work, we propose a new regime to mitigate these drawbacks. We replace the global-based compressive sensing used in the existing L2C2 by the local block (patch) based compressive sensing. We use a single sensor for each block, rather than for the entire image, thus forming a multiple but spatially parallel sensor L2C2.

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Authors:
Gang Huang, Hong Jiang, Paul Wilford
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17 September 2017 - 11:10am
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L2C2_ICIP2017_submit.pdf

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[1] Gang Huang, Hong Jiang, Paul Wilford, "Block-wise Lensless Compressive Camera", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2214. Accessed: Apr. 18, 2019.
@article{2214-17,
url = {http://sigport.org/2214},
author = {Gang Huang; Hong Jiang; Paul Wilford },
publisher = {IEEE SigPort},
title = {Block-wise Lensless Compressive Camera},
year = {2017} }
TY - EJOUR
T1 - Block-wise Lensless Compressive Camera
AU - Gang Huang; Hong Jiang; Paul Wilford
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2214
ER -
Gang Huang, Hong Jiang, Paul Wilford. (2017). Block-wise Lensless Compressive Camera. IEEE SigPort. http://sigport.org/2214
Gang Huang, Hong Jiang, Paul Wilford, 2017. Block-wise Lensless Compressive Camera. Available at: http://sigport.org/2214.
Gang Huang, Hong Jiang, Paul Wilford. (2017). "Block-wise Lensless Compressive Camera." Web.
1. Gang Huang, Hong Jiang, Paul Wilford. Block-wise Lensless Compressive Camera [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2214

DIY Sky Imager For Weather Observation


In this tutorial, we describe how to design a Whole Sky Imager from off-the-shelf components. Subsequently, we use signal processing techniques to derive instantaneous cloud coverage value from the captured images.

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Authors:
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler
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27 July 2016 - 11:36pm
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DIY Sky Imager Project.pdf

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[1] Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler, "DIY Sky Imager For Weather Observation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1136. Accessed: Apr. 18, 2019.
@article{1136-16,
url = {http://sigport.org/1136},
author = {Soumyabrata Dev; Florian M. Savoy; Yee Hui Lee; Stefan Winkler },
publisher = {IEEE SigPort},
title = {DIY Sky Imager For Weather Observation},
year = {2016} }
TY - EJOUR
T1 - DIY Sky Imager For Weather Observation
AU - Soumyabrata Dev; Florian M. Savoy; Yee Hui Lee; Stefan Winkler
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1136
ER -
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler. (2016). DIY Sky Imager For Weather Observation. IEEE SigPort. http://sigport.org/1136
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler, 2016. DIY Sky Imager For Weather Observation. Available at: http://sigport.org/1136.
Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler. (2016). "DIY Sky Imager For Weather Observation." Web.
1. Soumyabrata Dev, Florian M. Savoy, Yee Hui Lee, Stefan Winkler. DIY Sky Imager For Weather Observation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1136

A HIGH PERFORMANCE BASEBAND INSTRUMENT


Testing complex digital signal processors (DSPs) requires a development platform with sufficient
signal bandwidth and system performance to fully exercise the DSP. Without a development plat-
form, verification of DSPs would be limited to monitoring test output signals for an indication of
performance and successful operation. In addition, a development platform with high-speed analog
input and output interfaces to the DSP system allows it to be used directly in many sophisticated

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Authors:
Jeremy Webb, Bevan Baas
Submitted On:
30 June 2016 - 2:14am
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jwwebb.sigport.6.29.2016.pdf

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[1] Jeremy Webb, Bevan Baas, "A HIGH PERFORMANCE BASEBAND INSTRUMENT", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1130. Accessed: Apr. 18, 2019.
@article{1130-16,
url = {http://sigport.org/1130},
author = {Jeremy Webb; Bevan Baas },
publisher = {IEEE SigPort},
title = {A HIGH PERFORMANCE BASEBAND INSTRUMENT},
year = {2016} }
TY - EJOUR
T1 - A HIGH PERFORMANCE BASEBAND INSTRUMENT
AU - Jeremy Webb; Bevan Baas
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1130
ER -
Jeremy Webb, Bevan Baas. (2016). A HIGH PERFORMANCE BASEBAND INSTRUMENT. IEEE SigPort. http://sigport.org/1130
Jeremy Webb, Bevan Baas, 2016. A HIGH PERFORMANCE BASEBAND INSTRUMENT. Available at: http://sigport.org/1130.
Jeremy Webb, Bevan Baas. (2016). "A HIGH PERFORMANCE BASEBAND INSTRUMENT." Web.
1. Jeremy Webb, Bevan Baas. A HIGH PERFORMANCE BASEBAND INSTRUMENT [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1130

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