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Sensor and Relay Networks

Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System

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Authors:
Baofeng Ji,Bingbing Xing,Huahong Ma,Chunguo Li,Hong Wen,Luxi Yang
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5 July 2018 - 8:30am
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Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System.ppt

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[1] Baofeng Ji,Bingbing Xing,Huahong Ma,Chunguo Li,Hong Wen,Luxi Yang, "Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3360. Accessed: Aug. 21, 2018.
@article{3360-18,
url = {http://sigport.org/3360},
author = {Baofeng Ji;Bingbing Xing;Huahong Ma;Chunguo Li;Hong Wen;Luxi Yang },
publisher = {IEEE SigPort},
title = {Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System},
year = {2018} }
TY - EJOUR
T1 - Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System
AU - Baofeng Ji;Bingbing Xing;Huahong Ma;Chunguo Li;Hong Wen;Luxi Yang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3360
ER -
Baofeng Ji,Bingbing Xing,Huahong Ma,Chunguo Li,Hong Wen,Luxi Yang. (2018). Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System. IEEE SigPort. http://sigport.org/3360
Baofeng Ji,Bingbing Xing,Huahong Ma,Chunguo Li,Hong Wen,Luxi Yang, 2018. Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System. Available at: http://sigport.org/3360.
Baofeng Ji,Bingbing Xing,Huahong Ma,Chunguo Li,Hong Wen,Luxi Yang. (2018). "Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System." Web.
1. Baofeng Ji,Bingbing Xing,Huahong Ma,Chunguo Li,Hong Wen,Luxi Yang. Performance Analysis of Multi-hop Relaying Cooperation for Internet-of-things System [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3360

A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery


To strike a balance between energy efficiency and data quality control, this paper proposes a Neyman-Pearson type sensor censoring scheme for distributed sparse signal recovery via compressive-sensing based on wireless sensor networks. In the proposed approach, each sensor node employs a sparse sensing vector with known support for data compression, meanwhile enabling making local inference about the unknown support of the sparse signal vector of interest.

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Authors:
Jwo-Yuh Wu, Ming-Hsun Yang, and Tsang-Yi Wang
Submitted On:
1 July 2018 - 1:04am
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SAM_2018_Poster_New.pdf

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[1] Jwo-Yuh Wu, Ming-Hsun Yang, and Tsang-Yi Wang, "A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3345. Accessed: Aug. 21, 2018.
@article{3345-18,
url = {http://sigport.org/3345},
author = {Jwo-Yuh Wu; Ming-Hsun Yang; and Tsang-Yi Wang },
publisher = {IEEE SigPort},
title = {A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery},
year = {2018} }
TY - EJOUR
T1 - A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery
AU - Jwo-Yuh Wu; Ming-Hsun Yang; and Tsang-Yi Wang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3345
ER -
Jwo-Yuh Wu, Ming-Hsun Yang, and Tsang-Yi Wang. (2018). A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery. IEEE SigPort. http://sigport.org/3345
Jwo-Yuh Wu, Ming-Hsun Yang, and Tsang-Yi Wang, 2018. A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery. Available at: http://sigport.org/3345.
Jwo-Yuh Wu, Ming-Hsun Yang, and Tsang-Yi Wang. (2018). "A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery." Web.
1. Jwo-Yuh Wu, Ming-Hsun Yang, and Tsang-Yi Wang. A Neyman-Pearson Type Sensor Censoring Scheme for Compressive Distributed Sparse Signal Recovery [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3345

Tracking Multiple Evolving Threats With Cluttered Surveillance Observations


Many threats in the form of human actions (terrorist attacks, military actions, etc.) can be stochastically modeled by someone with relevant expert knowledge. In this work, a threat is taken to be a modeled sequence of actions that evolve over time and culminate at some ultimate goal. A model would be a hypothesis as to how a threat would develop, and what kind of observable evidence it would produce along the way. This modeling method allows us to attempt detection using the preliminary evidence of a threat.

SAM_Paper.pdf

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Authors:
Zachariah Sutton, Yaakov Bar-Shalom
Submitted On:
28 June 2018 - 7:18am
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SAM_Paper.pdf

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[1] Zachariah Sutton, Yaakov Bar-Shalom, "Tracking Multiple Evolving Threats With Cluttered Surveillance Observations", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3333. Accessed: Aug. 21, 2018.
@article{3333-18,
url = {http://sigport.org/3333},
author = {Zachariah Sutton; Yaakov Bar-Shalom },
publisher = {IEEE SigPort},
title = {Tracking Multiple Evolving Threats With Cluttered Surveillance Observations},
year = {2018} }
TY - EJOUR
T1 - Tracking Multiple Evolving Threats With Cluttered Surveillance Observations
AU - Zachariah Sutton; Yaakov Bar-Shalom
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3333
ER -
Zachariah Sutton, Yaakov Bar-Shalom. (2018). Tracking Multiple Evolving Threats With Cluttered Surveillance Observations. IEEE SigPort. http://sigport.org/3333
Zachariah Sutton, Yaakov Bar-Shalom, 2018. Tracking Multiple Evolving Threats With Cluttered Surveillance Observations. Available at: http://sigport.org/3333.
Zachariah Sutton, Yaakov Bar-Shalom. (2018). "Tracking Multiple Evolving Threats With Cluttered Surveillance Observations." Web.
1. Zachariah Sutton, Yaakov Bar-Shalom. Tracking Multiple Evolving Threats With Cluttered Surveillance Observations [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3333

Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion


In this paper a method for distributed detection for scenarios when there is no explicit knowledge of the probability models associated with the hypotheses is proposed. The underlying distributions are accurately learned from the data by bootstrapping. We propose using a nonparametric one-sample Anderson-Darling test locally at each sensor. The one-sample version of the test gives superior performance in comparison to the two-sample alternative. The local decision statistics, in particular p-values are then sent to a fusion center to make the final decision.

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Authors:
Topi Halme, Visa Koivunen
Submitted On:
3 June 2018 - 4:59am
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DSW_poster_VK.pdf

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[1] Topi Halme, Visa Koivunen, "Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3232. Accessed: Aug. 21, 2018.
@article{3232-18,
url = {http://sigport.org/3232},
author = {Topi Halme; Visa Koivunen },
publisher = {IEEE SigPort},
title = {Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion},
year = {2018} }
TY - EJOUR
T1 - Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion
AU - Topi Halme; Visa Koivunen
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3232
ER -
Topi Halme, Visa Koivunen. (2018). Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion. IEEE SigPort. http://sigport.org/3232
Topi Halme, Visa Koivunen, 2018. Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion. Available at: http://sigport.org/3232.
Topi Halme, Visa Koivunen. (2018). "Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion." Web.
1. Topi Halme, Visa Koivunen. Nonparametric Distributed Detection Using One-Sample Anderson-Darling Test and p-value Fusion [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3232

Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization


Sonobuoy fields, comprising a network of transmitters and receivers, are commonly deployed to find and track underwater targets. For a given environment and sonobuoy field layout, the performance of such a field depends on the scheduling, that is, deciding which source should transmit, and which from a library of available waveforms should be transmitted at any given time. In this paper, we propose a novel scheduling framework based on multi-objective optimization. Specifically, we pose the two tasks of the sonobuoy field—tracking and searching—as separate, competing, objective functions.

Sonar_Slides.pdf

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Authors:
Daniel Angley, Sofia Suvorova, Branko Ristic, Bill Moran, Fiona Fletcher, Han Gaetjens, Sergey Simakov
Submitted On:
18 April 2018 - 10:44am
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Slides

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[1] Daniel Angley, Sofia Suvorova, Branko Ristic, Bill Moran, Fiona Fletcher, Han Gaetjens, Sergey Simakov, "Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2966. Accessed: Aug. 21, 2018.
@article{2966-18,
url = {http://sigport.org/2966},
author = {Daniel Angley; Sofia Suvorova; Branko Ristic; Bill Moran; Fiona Fletcher; Han Gaetjens; Sergey Simakov },
publisher = {IEEE SigPort},
title = {Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization},
year = {2018} }
TY - EJOUR
T1 - Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization
AU - Daniel Angley; Sofia Suvorova; Branko Ristic; Bill Moran; Fiona Fletcher; Han Gaetjens; Sergey Simakov
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2966
ER -
Daniel Angley, Sofia Suvorova, Branko Ristic, Bill Moran, Fiona Fletcher, Han Gaetjens, Sergey Simakov. (2018). Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization. IEEE SigPort. http://sigport.org/2966
Daniel Angley, Sofia Suvorova, Branko Ristic, Bill Moran, Fiona Fletcher, Han Gaetjens, Sergey Simakov, 2018. Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization. Available at: http://sigport.org/2966.
Daniel Angley, Sofia Suvorova, Branko Ristic, Bill Moran, Fiona Fletcher, Han Gaetjens, Sergey Simakov. (2018). "Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization." Web.
1. Daniel Angley, Sofia Suvorova, Branko Ristic, Bill Moran, Fiona Fletcher, Han Gaetjens, Sergey Simakov. Scheduling of Multistatic Sonobuoy Fields using Multi-Objective Optimization [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2966

A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks

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Authors:
Masahiro Yukawa, Renato Cavalcante, Armin Dekorsy
Submitted On:
12 April 2018 - 11:11am
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ANTposter.pdf

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[1] Masahiro Yukawa, Renato Cavalcante, Armin Dekorsy, "A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2382. Accessed: Aug. 21, 2018.
@article{2382-18,
url = {http://sigport.org/2382},
author = {Masahiro Yukawa; Renato Cavalcante; Armin Dekorsy },
publisher = {IEEE SigPort},
title = {A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks},
year = {2018} }
TY - EJOUR
T1 - A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks
AU - Masahiro Yukawa; Renato Cavalcante; Armin Dekorsy
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2382
ER -
Masahiro Yukawa, Renato Cavalcante, Armin Dekorsy. (2018). A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks. IEEE SigPort. http://sigport.org/2382
Masahiro Yukawa, Renato Cavalcante, Armin Dekorsy, 2018. A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks. Available at: http://sigport.org/2382.
Masahiro Yukawa, Renato Cavalcante, Armin Dekorsy. (2018). "A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks." Web.
1. Masahiro Yukawa, Renato Cavalcante, Armin Dekorsy. A hybrid dictionary approach for distributed kernel adaptive filtering in diffusion networks [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2382

PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS


Optimal parameter estimation requires simultaneous processing of all available measurements.
The complexity of this task may become too large when measurements from two or more multimodal sensor networks are avaliable.
In such cases, fusion of estimates obtained from each data set separately may be practical.
In this paper, we derive the optimal linear combination of the possibly non-linear estimators, and propose sub-optimal weightings.
We analyze the asymptotic performance gain of the first suboptimal approach with respect to the individual optimal estimates.

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Authors:
Inbar Fijalkow, Elad Heiman
Submitted On:
1 March 2017 - 10:06am
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HMY_ICASSP2017.pdf

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[1] Inbar Fijalkow, Elad Heiman, "PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1555. Accessed: Aug. 21, 2018.
@article{1555-17,
url = {http://sigport.org/1555},
author = {Inbar Fijalkow; Elad Heiman },
publisher = {IEEE SigPort},
title = {PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS},
year = {2017} }
TY - EJOUR
T1 - PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS
AU - Inbar Fijalkow; Elad Heiman
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1555
ER -
Inbar Fijalkow, Elad Heiman. (2017). PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS. IEEE SigPort. http://sigport.org/1555
Inbar Fijalkow, Elad Heiman, 2017. PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS. Available at: http://sigport.org/1555.
Inbar Fijalkow, Elad Heiman. (2017). "PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS." Web.
1. Inbar Fijalkow, Elad Heiman. PARAMETER ESTIMATION FROM HETEROGENEOUS/MULTIMODAL DATA SETS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1555

Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems

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Authors:
Ozlem Tugfe Demir, Temel Engin Tuncer
Submitted On:
18 March 2016 - 12:51pm
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icassp_relayv1.pdf

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[1] Ozlem Tugfe Demir, Temel Engin Tuncer, "Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/771. Accessed: Aug. 21, 2018.
@article{771-16,
url = {http://sigport.org/771},
author = {Ozlem Tugfe Demir; Temel Engin Tuncer },
publisher = {IEEE SigPort},
title = {Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems},
year = {2016} }
TY - EJOUR
T1 - Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems
AU - Ozlem Tugfe Demir; Temel Engin Tuncer
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/771
ER -
Ozlem Tugfe Demir, Temel Engin Tuncer. (2016). Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems. IEEE SigPort. http://sigport.org/771
Ozlem Tugfe Demir, Temel Engin Tuncer, 2016. Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems. Available at: http://sigport.org/771.
Ozlem Tugfe Demir, Temel Engin Tuncer. (2016). "Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems." Web.
1. Ozlem Tugfe Demir, Temel Engin Tuncer. Distributed Beamforming in Relay Networks for Energy Harvesting Multi-Group Multicast Systems [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/771