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Audio and Acoustic Signal Processing

Bluetooth based Indoor Localization using Triplet Embeddings

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Authors:
Karel Mundnich, Benjamin Girault, Shrikanth Narayanan
Submitted On:
7 May 2019 - 2:43pm
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[1] Karel Mundnich, Benjamin Girault, Shrikanth Narayanan, "Bluetooth based Indoor Localization using Triplet Embeddings", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3945. Accessed: Oct. 17, 2019.
@article{3945-19,
url = {http://sigport.org/3945},
author = {Karel Mundnich; Benjamin Girault; Shrikanth Narayanan },
publisher = {IEEE SigPort},
title = {Bluetooth based Indoor Localization using Triplet Embeddings},
year = {2019} }
TY - EJOUR
T1 - Bluetooth based Indoor Localization using Triplet Embeddings
AU - Karel Mundnich; Benjamin Girault; Shrikanth Narayanan
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3945
ER -
Karel Mundnich, Benjamin Girault, Shrikanth Narayanan. (2019). Bluetooth based Indoor Localization using Triplet Embeddings. IEEE SigPort. http://sigport.org/3945
Karel Mundnich, Benjamin Girault, Shrikanth Narayanan, 2019. Bluetooth based Indoor Localization using Triplet Embeddings. Available at: http://sigport.org/3945.
Karel Mundnich, Benjamin Girault, Shrikanth Narayanan. (2019). "Bluetooth based Indoor Localization using Triplet Embeddings." Web.
1. Karel Mundnich, Benjamin Girault, Shrikanth Narayanan. Bluetooth based Indoor Localization using Triplet Embeddings [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3945

DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS


In this paper, we propose a statistical framework to prune feature maps in 1-D deep convolutional networks. SoundNet is a pre-trained deep convolutional network that accepts raw audio samples as input. The feature maps generated at various layers of SoundNet have redundancy, which can be identified by statistical analysis. These redundant feature maps can be pruned from the network with a very minor reduction in the capability of the network.

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Authors:
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar
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7 May 2019 - 1:19am
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[1] Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar , "DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3919. Accessed: Oct. 17, 2019.
@article{3919-19,
url = {http://sigport.org/3919},
author = { Arshdeep Singh ; Padmanabhan Rajan ; Arnav Bhavsar },
publisher = {IEEE SigPort},
title = {DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS},
year = {2019} }
TY - EJOUR
T1 - DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS
AU - Arshdeep Singh ; Padmanabhan Rajan ; Arnav Bhavsar
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3919
ER -
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar . (2019). DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS. IEEE SigPort. http://sigport.org/3919
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar , 2019. DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS. Available at: http://sigport.org/3919.
Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar . (2019). "DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS." Web.
1. Arshdeep Singh , Padmanabhan Rajan , Arnav Bhavsar . DEEP HIDDEN ANALYSIS: A STATISTICAL FRAMEWORK TO PRUNE FEATURE MAPS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3919

Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game


This paper studies the problem of Stackelberg game based distributed power allocation for spectral coexisting multistatic radar and communication systems. The strategy aims to minimize the radiated power of each radar by optimizing transmit power allocation for a desired signal-to-interference-plus-noise ratio (SINR) meanwhile the communication base station (CBS) is protected from the interference of radar transmissions. We formulate this distributed power allocation process as a Stackelberg game, where the CBS is a leader and the radars are the followers.

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Authors:
Chenguang Shi, Fei Wang, Sana Salous, Jianjiang Zhou
Submitted On:
14 February 2019 - 10:01pm
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[1] Chenguang Shi, Fei Wang, Sana Salous, Jianjiang Zhou, "Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/3850. Accessed: Oct. 17, 2019.
@article{3850-19,
url = {http://sigport.org/3850},
author = {Chenguang Shi; Fei Wang; Sana Salous; Jianjiang Zhou },
publisher = {IEEE SigPort},
title = {Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game},
year = {2019} }
TY - EJOUR
T1 - Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game
AU - Chenguang Shi; Fei Wang; Sana Salous; Jianjiang Zhou
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/3850
ER -
Chenguang Shi, Fei Wang, Sana Salous, Jianjiang Zhou. (2019). Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game. IEEE SigPort. http://sigport.org/3850
Chenguang Shi, Fei Wang, Sana Salous, Jianjiang Zhou, 2019. Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game. Available at: http://sigport.org/3850.
Chenguang Shi, Fei Wang, Sana Salous, Jianjiang Zhou. (2019). "Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game." Web.
1. Chenguang Shi, Fei Wang, Sana Salous, Jianjiang Zhou. Distributed Power Allocation for Spectral Coexisting Multistatic Radar and Communication Systems Based on Stackelberg Game [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/3850

Fast phase-difference-based DoA estimation using random ferns


Direction of arrival (DOA) information of a signal is important in communications, localization, object tracking and so on. Frequency-domain-based time-delay estimation is capable of achieving DOA in subsample accuracy; however, it suffers from the phase wrapping problem. In this paper, a frequency-diversity based method is proposed to overcome the phase wrapping problem. Inspired by the machine learning technique of random ferns, an algorithm is proposed to speed up the search procedure.

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Authors:
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri
Submitted On:
27 November 2018 - 3:31am
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[1] Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri, "Fast phase-difference-based DoA estimation using random ferns", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3807. Accessed: Oct. 17, 2019.
@article{3807-18,
url = {http://sigport.org/3807},
author = {Hui Chen; Tarig Ballal; Tareq Y. Al-Naffouri },
publisher = {IEEE SigPort},
title = {Fast phase-difference-based DoA estimation using random ferns},
year = {2018} }
TY - EJOUR
T1 - Fast phase-difference-based DoA estimation using random ferns
AU - Hui Chen; Tarig Ballal; Tareq Y. Al-Naffouri
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3807
ER -
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri. (2018). Fast phase-difference-based DoA estimation using random ferns. IEEE SigPort. http://sigport.org/3807
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri, 2018. Fast phase-difference-based DoA estimation using random ferns. Available at: http://sigport.org/3807.
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri. (2018). "Fast phase-difference-based DoA estimation using random ferns." Web.
1. Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri. Fast phase-difference-based DoA estimation using random ferns [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3807

Predicting Power Outages Using Graph Neural Networks


Power outages have a major impact on economic development due to the dependence of (virtually all) productive sectors on electric power. Thus, many resources within the scientific and engineering communities have been employed to improve the efficiency and reliability of power grids. In particular, we consider the problem of predicting power outages based on the current weather conditions. Weather measurements taken by a sensor network naturally fit within the graph signal processing framework since the measurements are related by the relative position of the sensors.

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Authors:
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Submitted On:
26 November 2018 - 10:11pm
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[1] Damian Owerko, Fernando Gama, Alejandro Ribeiro, "Predicting Power Outages Using Graph Neural Networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3800. Accessed: Oct. 17, 2019.
@article{3800-18,
url = {http://sigport.org/3800},
author = {Damian Owerko; Fernando Gama; Alejandro Ribeiro },
publisher = {IEEE SigPort},
title = {Predicting Power Outages Using Graph Neural Networks},
year = {2018} }
TY - EJOUR
T1 - Predicting Power Outages Using Graph Neural Networks
AU - Damian Owerko; Fernando Gama; Alejandro Ribeiro
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3800
ER -
Damian Owerko, Fernando Gama, Alejandro Ribeiro. (2018). Predicting Power Outages Using Graph Neural Networks. IEEE SigPort. http://sigport.org/3800
Damian Owerko, Fernando Gama, Alejandro Ribeiro, 2018. Predicting Power Outages Using Graph Neural Networks. Available at: http://sigport.org/3800.
Damian Owerko, Fernando Gama, Alejandro Ribeiro. (2018). "Predicting Power Outages Using Graph Neural Networks." Web.
1. Damian Owerko, Fernando Gama, Alejandro Ribeiro. Predicting Power Outages Using Graph Neural Networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3800

Fast phase-difference-based DoA estimation using random ferns

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Authors:
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri
Submitted On:
27 November 2018 - 3:31am
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[1] Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri, "Fast phase-difference-based DoA estimation using random ferns", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3798. Accessed: Oct. 17, 2019.
@article{3798-18,
url = {http://sigport.org/3798},
author = {Hui Chen; Tarig Ballal; Tareq Y. Al-Naffouri },
publisher = {IEEE SigPort},
title = {Fast phase-difference-based DoA estimation using random ferns},
year = {2018} }
TY - EJOUR
T1 - Fast phase-difference-based DoA estimation using random ferns
AU - Hui Chen; Tarig Ballal; Tareq Y. Al-Naffouri
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3798
ER -
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri. (2018). Fast phase-difference-based DoA estimation using random ferns. IEEE SigPort. http://sigport.org/3798
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri, 2018. Fast phase-difference-based DoA estimation using random ferns. Available at: http://sigport.org/3798.
Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri. (2018). "Fast phase-difference-based DoA estimation using random ferns." Web.
1. Hui Chen, Tarig Ballal, Tareq Y. Al-Naffouri. Fast phase-difference-based DoA estimation using random ferns [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3798

Robust Multi-User Analog Beamforming in mmWave MIMO Systems


In this paper, we propose a robust analog-only beamforming scheme for the downlink multi-user systems, which not only suppresses the interference and enhances the beamform- ing gain, but also provides robustness against imperfect channel state information (CSI). We strike a balance between the average beamforming gain and the inter-user interference by formulating a multi-objective problem. A probabilistic objective of leakage interference power is formulated to alleviate the effects of the channel estimation and feedback quantization errors.

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Authors:
Lisi Jiang, Hamid Jafarkhani
Submitted On:
26 November 2018 - 7:06pm
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[1] Lisi Jiang, Hamid Jafarkhani, "Robust Multi-User Analog Beamforming in mmWave MIMO Systems", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3794. Accessed: Oct. 17, 2019.
@article{3794-18,
url = {http://sigport.org/3794},
author = {Lisi Jiang; Hamid Jafarkhani },
publisher = {IEEE SigPort},
title = {Robust Multi-User Analog Beamforming in mmWave MIMO Systems},
year = {2018} }
TY - EJOUR
T1 - Robust Multi-User Analog Beamforming in mmWave MIMO Systems
AU - Lisi Jiang; Hamid Jafarkhani
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3794
ER -
Lisi Jiang, Hamid Jafarkhani. (2018). Robust Multi-User Analog Beamforming in mmWave MIMO Systems. IEEE SigPort. http://sigport.org/3794
Lisi Jiang, Hamid Jafarkhani, 2018. Robust Multi-User Analog Beamforming in mmWave MIMO Systems. Available at: http://sigport.org/3794.
Lisi Jiang, Hamid Jafarkhani. (2018). "Robust Multi-User Analog Beamforming in mmWave MIMO Systems." Web.
1. Lisi Jiang, Hamid Jafarkhani. Robust Multi-User Analog Beamforming in mmWave MIMO Systems [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3794

Defending DNN Adversarial Attacks with Pruning and Logits Augmentation


Deep neural networks (DNNs) have been shown to be powerful models and perform extremely well on many complicated artificial intelligent tasks. However, recent research found that these powerful models are vulnerable to adversarial attacks, i.e., intentionally added imperceptible perturbations to DNN inputs can easily mislead the DNNs with extremely high confidence. In this work, we enhance the robustness of DNNs under adversarial attacks by using pruning method and logits augmentation, we achieve both effective defense against adversarial examples and DNN model compression.

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Authors:
Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin
Submitted On:
24 November 2018 - 8:54am
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[1] Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin, "Defending DNN Adversarial Attacks with Pruning and Logits Augmentation", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3769. Accessed: Oct. 17, 2019.
@article{3769-18,
url = {http://sigport.org/3769},
author = {Xiao Wang; Shaokai Ye; Pu Zhao; Xue Lin },
publisher = {IEEE SigPort},
title = {Defending DNN Adversarial Attacks with Pruning and Logits Augmentation},
year = {2018} }
TY - EJOUR
T1 - Defending DNN Adversarial Attacks with Pruning and Logits Augmentation
AU - Xiao Wang; Shaokai Ye; Pu Zhao; Xue Lin
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3769
ER -
Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin. (2018). Defending DNN Adversarial Attacks with Pruning and Logits Augmentation. IEEE SigPort. http://sigport.org/3769
Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin, 2018. Defending DNN Adversarial Attacks with Pruning and Logits Augmentation. Available at: http://sigport.org/3769.
Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin. (2018). "Defending DNN Adversarial Attacks with Pruning and Logits Augmentation." Web.
1. Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin. Defending DNN Adversarial Attacks with Pruning and Logits Augmentation [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3769

60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT


This paper presents a large-scale fading channel model at the 60 GHz band. This model is based on the measurement campaign that our team conducted at Boise Airport and Boise State University. The close-in reference path loss and floating-intercept path loss models with both statistical and stochastic approaches are investigated for these environments. The measurements were collected at several different locations in line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios using a high gain directional antenna.

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Authors:
Mahfuza Khatun, Hani Mehrpouyan, David Matolak
Submitted On:
28 November 2018 - 2:06am
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[1] Mahfuza Khatun, Hani Mehrpouyan, David Matolak, "60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3762. Accessed: Oct. 17, 2019.
@article{3762-18,
url = {http://sigport.org/3762},
author = {Mahfuza Khatun; Hani Mehrpouyan; David Matolak },
publisher = {IEEE SigPort},
title = {60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT},
year = {2018} }
TY - EJOUR
T1 - 60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT
AU - Mahfuza Khatun; Hani Mehrpouyan; David Matolak
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3762
ER -
Mahfuza Khatun, Hani Mehrpouyan, David Matolak. (2018). 60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT. IEEE SigPort. http://sigport.org/3762
Mahfuza Khatun, Hani Mehrpouyan, David Matolak, 2018. 60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT. Available at: http://sigport.org/3762.
Mahfuza Khatun, Hani Mehrpouyan, David Matolak. (2018). "60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT." Web.
1. Mahfuza Khatun, Hani Mehrpouyan, David Matolak. 60-GHZ MILLIMETER-WAVE PATHLOSS MEASUREMENTS IN BOISE AIRPORT [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3762

A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging


In this paper, we consider two practical coded compressive imaging techniques. We investigate the optimal number of measurements under quadratic signal-to-noise-ratio (SNR) decrease. We focus on imaging scenarios in both real and complex vector spaces. In real vector spaces, we consider focal plane array (FPA) based super-resolution imaging with a constant measurement time constraint. Our model is comprised of a spatial light modulator and a low resolution FPA for modulating and sampling the incoming light intensity, respectively.

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Authors:
Oğuzhan Fatih Kar, Alper Güngör, Serhat Ilbey, Can Barış Top, H. Emre Güven
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23 November 2018 - 6:01am
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[1] Oğuzhan Fatih Kar, Alper Güngör, Serhat Ilbey, Can Barış Top, H. Emre Güven, "A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3741. Accessed: Oct. 17, 2019.
@article{3741-18,
url = {http://sigport.org/3741},
author = {Oğuzhan Fatih Kar; Alper Güngör; Serhat Ilbey; Can Barış Top; H. Emre Güven },
publisher = {IEEE SigPort},
title = {A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging},
year = {2018} }
TY - EJOUR
T1 - A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging
AU - Oğuzhan Fatih Kar; Alper Güngör; Serhat Ilbey; Can Barış Top; H. Emre Güven
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3741
ER -
Oğuzhan Fatih Kar, Alper Güngör, Serhat Ilbey, Can Barış Top, H. Emre Güven. (2018). A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging. IEEE SigPort. http://sigport.org/3741
Oğuzhan Fatih Kar, Alper Güngör, Serhat Ilbey, Can Barış Top, H. Emre Güven, 2018. A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging. Available at: http://sigport.org/3741.
Oğuzhan Fatih Kar, Alper Güngör, Serhat Ilbey, Can Barış Top, H. Emre Güven. (2018). "A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging." Web.
1. Oğuzhan Fatih Kar, Alper Güngör, Serhat Ilbey, Can Barış Top, H. Emre Güven. A Performance Analysis on the Optimal Number of Measurements for Coded Compressive Imaging [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3741

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