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Audio and Acoustic Signal Processing

On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels


The Gamma-Gamma distribution has recently emerged in a number of applications ranging from modeling scattering and reverberation in sonar and radar systems to modeling atmospheric turbulence in wireless optical channels. In this respect, assessing the outage probability achieved by some diversity techniques over this kind of channels is of major practical importance. In many circumstances, this is intimately related to the difficult question of analyzing the statistics of a sum of Gamma-Gamma random variables. Answering this question is not a simple matter.

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Authors:
Chaouki ben Issaid, Nadhir ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone
Submitted On:
7 December 2016 - 1:39am
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Presentation session at GlobalSip'16 conference

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[1] Chaouki ben Issaid, Nadhir ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone, "On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1397. Accessed: May. 25, 2017.
@article{1397-16,
url = {http://sigport.org/1397},
author = {Chaouki ben Issaid; Nadhir ben Rached; Abla Kammoun; Mohamed-Slim Alouini; Raul Tempone },
publisher = {IEEE SigPort},
title = {On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels},
year = {2016} }
TY - EJOUR
T1 - On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels
AU - Chaouki ben Issaid; Nadhir ben Rached; Abla Kammoun; Mohamed-Slim Alouini; Raul Tempone
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1397
ER -
Chaouki ben Issaid, Nadhir ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone. (2016). On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels. IEEE SigPort. http://sigport.org/1397
Chaouki ben Issaid, Nadhir ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone, 2016. On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels. Available at: http://sigport.org/1397.
Chaouki ben Issaid, Nadhir ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone. (2016). "On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels." Web.
1. Chaouki ben Issaid, Nadhir ben Rached, Abla Kammoun, Mohamed-Slim Alouini, Raul Tempone. On the Sum of Gamma-Gamma Variates with Application to the Fast Outage Probability Evaluation Over Fading Channels [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1397

Hidden Markov Model-based Gesture Recognition with FMCW Radar


In this paper we present experimental results for the development
of a gesture recognition system using a 77 GHz FMCW
radar system. We measure the micro-Doppler signature of a
gesturing hand to construct an energy distribution in velocity
space over time. A gesturing hand is fundamentally a dynamical
system with unobservable “state” (i.e. the name of the gesture)
which determines the sequence of associated observable
velocity-energy distributions, so a Hidden Markov Model is
used to for gesture recognition, a more tailored approach than

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Authors:
Greg Malysa, Dan Wang, Lorin Netsch, Murtaza Ali
Submitted On:
6 December 2016 - 12:06pm
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20161208_globalsip_1330.pdf

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[1] Greg Malysa, Dan Wang, Lorin Netsch, Murtaza Ali, "Hidden Markov Model-based Gesture Recognition with FMCW Radar", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1366. Accessed: May. 25, 2017.
@article{1366-16,
url = {http://sigport.org/1366},
author = {Greg Malysa; Dan Wang; Lorin Netsch; Murtaza Ali },
publisher = {IEEE SigPort},
title = {Hidden Markov Model-based Gesture Recognition with FMCW Radar},
year = {2016} }
TY - EJOUR
T1 - Hidden Markov Model-based Gesture Recognition with FMCW Radar
AU - Greg Malysa; Dan Wang; Lorin Netsch; Murtaza Ali
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1366
ER -
Greg Malysa, Dan Wang, Lorin Netsch, Murtaza Ali. (2016). Hidden Markov Model-based Gesture Recognition with FMCW Radar. IEEE SigPort. http://sigport.org/1366
Greg Malysa, Dan Wang, Lorin Netsch, Murtaza Ali, 2016. Hidden Markov Model-based Gesture Recognition with FMCW Radar. Available at: http://sigport.org/1366.
Greg Malysa, Dan Wang, Lorin Netsch, Murtaza Ali. (2016). "Hidden Markov Model-based Gesture Recognition with FMCW Radar." Web.
1. Greg Malysa, Dan Wang, Lorin Netsch, Murtaza Ali. Hidden Markov Model-based Gesture Recognition with FMCW Radar [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1366

CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS


An attributed network has nodes with attribute vectors. For community detection on an attributed network, we exploit the attributes to disentangle the potentially mixed topological structures. We describe a multiplex representation scheme for overlapping community detection in attributed networks and find consensus communities across layers of different connection structures. We test the method on Twitter, Facebook and Google+ networks and the results are comparable to state of the art. We show that the use of attribute vectors improves detection accuracy.

poster.pdf

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Paper Details

Authors:
Han Wang
Submitted On:
5 December 2016 - 4:23pm
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poster.pdf

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[1] Han Wang, "CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1350. Accessed: May. 25, 2017.
@article{1350-16,
url = {http://sigport.org/1350},
author = {Han Wang },
publisher = {IEEE SigPort},
title = {CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS},
year = {2016} }
TY - EJOUR
T1 - CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS
AU - Han Wang
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1350
ER -
Han Wang. (2016). CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS. IEEE SigPort. http://sigport.org/1350
Han Wang, 2016. CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS. Available at: http://sigport.org/1350.
Han Wang. (2016). "CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS." Web.
1. Han Wang. CONSENSUS AND MULTIPLEX APPROACH FOR COMMUNITY DETECTION IN ATTRIBUTED NETWORKS [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1350

Sparse Representation of Human Auditory System


In this paper, three sparse models for the human auditory system are proposed. Biological studies shows that the haircells in the inner ear of the auditory system generate sparse codes from the output of cochlea filterbank. Here, we employ two mathematical sparse representation methods, which are Orthogonal Matching Pursuit (OMP) and K Singular Value Decomposition (K-SVD), in three different strategies for sparse representation of the output of cochlea filterbank that is modeled by a Gammatone filterbank.

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Authors:
Mohammad Edalatian,, Ali Asghar Soltani, Neda Faraji
Submitted On:
4 December 2016 - 1:33pm
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Sparse representation of Human Auditory System

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[1] Mohammad Edalatian,, Ali Asghar Soltani, Neda Faraji , "Sparse Representation of Human Auditory System", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1339. Accessed: May. 25, 2017.
@article{1339-16,
url = {http://sigport.org/1339},
author = {Mohammad Edalatian;; Ali Asghar Soltani; Neda Faraji },
publisher = {IEEE SigPort},
title = {Sparse Representation of Human Auditory System},
year = {2016} }
TY - EJOUR
T1 - Sparse Representation of Human Auditory System
AU - Mohammad Edalatian;; Ali Asghar Soltani; Neda Faraji
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1339
ER -
Mohammad Edalatian,, Ali Asghar Soltani, Neda Faraji . (2016). Sparse Representation of Human Auditory System. IEEE SigPort. http://sigport.org/1339
Mohammad Edalatian,, Ali Asghar Soltani, Neda Faraji , 2016. Sparse Representation of Human Auditory System. Available at: http://sigport.org/1339.
Mohammad Edalatian,, Ali Asghar Soltani, Neda Faraji . (2016). "Sparse Representation of Human Auditory System." Web.
1. Mohammad Edalatian,, Ali Asghar Soltani, Neda Faraji . Sparse Representation of Human Auditory System [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1339

GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION


Modeling a location-unaware sensor network as a simplicial complex, where simplices correspond to cliques in the communication graph, has proven useful for solving a number of coverage problems under certain conditions using algebraic topology. Several approaches to finding a sparse cover for a fenced sensor network are considered, including calculating homology changes locally, strong collapsing, and Euler characteristic collapsing.

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2 December 2016 - 7:22pm
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Moore-GlobalSIP2016_pdf.pdf

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[1] , "GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1333. Accessed: May. 25, 2017.
@article{1333-16,
url = {http://sigport.org/1333},
author = { },
publisher = {IEEE SigPort},
title = {GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION},
year = {2016} }
TY - EJOUR
T1 - GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1333
ER -
. (2016). GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION. IEEE SigPort. http://sigport.org/1333
, 2016. GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION. Available at: http://sigport.org/1333.
. (2016). "GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION." Web.
1. . GREEDY APPROACHES TO FINDING A SPARSE COVER IN A SENSOR NETWORK WITHOUT LOCATION INFORMATION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1333

Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink


We characterize third-dimension (3D) of channel measurements based on two dimension channel model with fully synchronize

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Authors:
Saeid Aghaeinezhadfirouzja ,Hui Liu ,Bin XIA ,Qun Luo and Weibin Guo
Submitted On:
29 November 2016 - 3:07am
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poster.pdf

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Final GlobalSIP 08-10-2016.pdf

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[1] Saeid Aghaeinezhadfirouzja ,Hui Liu ,Bin XIA ,Qun Luo and Weibin Guo, "Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1317. Accessed: May. 25, 2017.
@article{1317-16,
url = {http://sigport.org/1317},
author = {Saeid Aghaeinezhadfirouzja ;Hui Liu ;Bin XIA ;Qun Luo and Weibin Guo },
publisher = {IEEE SigPort},
title = {Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink},
year = {2016} }
TY - EJOUR
T1 - Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink
AU - Saeid Aghaeinezhadfirouzja ;Hui Liu ;Bin XIA ;Qun Luo and Weibin Guo
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1317
ER -
Saeid Aghaeinezhadfirouzja ,Hui Liu ,Bin XIA ,Qun Luo and Weibin Guo. (2016). Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink. IEEE SigPort. http://sigport.org/1317
Saeid Aghaeinezhadfirouzja ,Hui Liu ,Bin XIA ,Qun Luo and Weibin Guo, 2016. Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink. Available at: http://sigport.org/1317.
Saeid Aghaeinezhadfirouzja ,Hui Liu ,Bin XIA ,Qun Luo and Weibin Guo. (2016). "Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink." Web.
1. Saeid Aghaeinezhadfirouzja ,Hui Liu ,Bin XIA ,Qun Luo and Weibin Guo. Third dimension for measurement of multi user massive MIMO channels based on LTE advanced downlink [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1317

Action Classification from Motion Capture Data using Topological Data Analysis


This paper proposes a novel framework for activity recognition from 3D motion capture data using topological data analysis (TDA). We extract point clouds describing the oscillatory patterns of body joints from the principal components of their time series using Taken's delay embedding. Topological persistence from TDA is exploited to extract topological invariants of the constructed point clouds. We propose a feature extraction method from persistence diagrams in order to generate robust low dimensional features used for classification of different activities.

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Authors:
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton
Submitted On:
26 November 2016 - 11:07am
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Poster

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Presentation

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[1] Alireza Dirafzoon, Namita Lokare and Edgar Lobaton, "Action Classification from Motion Capture Data using Topological Data Analysis", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1310. Accessed: May. 25, 2017.
@article{1310-16,
url = {http://sigport.org/1310},
author = {Alireza Dirafzoon; Namita Lokare and Edgar Lobaton },
publisher = {IEEE SigPort},
title = {Action Classification from Motion Capture Data using Topological Data Analysis},
year = {2016} }
TY - EJOUR
T1 - Action Classification from Motion Capture Data using Topological Data Analysis
AU - Alireza Dirafzoon; Namita Lokare and Edgar Lobaton
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1310
ER -
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton. (2016). Action Classification from Motion Capture Data using Topological Data Analysis. IEEE SigPort. http://sigport.org/1310
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton, 2016. Action Classification from Motion Capture Data using Topological Data Analysis. Available at: http://sigport.org/1310.
Alireza Dirafzoon, Namita Lokare and Edgar Lobaton. (2016). "Action Classification from Motion Capture Data using Topological Data Analysis." Web.
1. Alireza Dirafzoon, Namita Lokare and Edgar Lobaton. Action Classification from Motion Capture Data using Topological Data Analysis [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1310

Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery


In this paper we propose a hierarchical activity clustering methodology which incorporates the use of topological persistence analysis. Our clustering methodology captures the hierarchies present in the data and is therefore able to show the dependencies that exist between these activities. We make use of an aggregate persistence diagram to select robust graphical structures present within the dataset. These models are stable over a bound and provide accurate classification results.

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Authors:
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton
Submitted On:
26 November 2016 - 11:17am
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Poster

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Presentation

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[1] Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton, "Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1309. Accessed: May. 25, 2017.
@article{1309-16,
url = {http://sigport.org/1309},
author = {Namita Lokare; Daniel Benavides; Sahil Juneja; Edgar Lobaton },
publisher = {IEEE SigPort},
title = {Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery},
year = {2016} }
TY - EJOUR
T1 - Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery
AU - Namita Lokare; Daniel Benavides; Sahil Juneja; Edgar Lobaton
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1309
ER -
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton. (2016). Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery. IEEE SigPort. http://sigport.org/1309
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton, 2016. Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery. Available at: http://sigport.org/1309.
Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton. (2016). "Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery." Web.
1. Namita Lokare, Daniel Benavides, Sahil Juneja, Edgar Lobaton. Hierarchical Activity Clustering Analysis for Robust Graphical Structure Recovery [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1309

Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia


The absence of manually annotated training data presents an obstacle for the development of machine-learning based NLP tools in Indonesia. Existing annotation tools lack a mobile-friendly interface which is a problem in Indonesia where most users access the internet using their smartphone. In this paper we propose the first mobile collaborative data annotation tool and evaluate it in an experiment involving 15 Indonesian students who annotated 1500 data records using their smartphones. Users confirmed

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Authors:
Lisa Madlberger, Ayu Purwarianti
Submitted On:
21 November 2016 - 10:49pm
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presentation_IALP2016_46.pdf

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[1] Lisa Madlberger, Ayu Purwarianti, "Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1290. Accessed: May. 25, 2017.
@article{1290-16,
url = {http://sigport.org/1290},
author = {Lisa Madlberger; Ayu Purwarianti },
publisher = {IEEE SigPort},
title = {Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia },
year = {2016} }
TY - EJOUR
T1 - Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia
AU - Lisa Madlberger; Ayu Purwarianti
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1290
ER -
Lisa Madlberger, Ayu Purwarianti. (2016). Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia . IEEE SigPort. http://sigport.org/1290
Lisa Madlberger, Ayu Purwarianti, 2016. Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia . Available at: http://sigport.org/1290.
Lisa Madlberger, Ayu Purwarianti. (2016). "Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia ." Web.
1. Lisa Madlberger, Ayu Purwarianti. Gotong Royong in NLP Research: A Mobile Tool for Collaborative Text Annotation in Indonesia [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1290

A Regression Approach to Valence-Arousal Ratings of Words from Word

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17 November 2016 - 6:54am
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A Regression Approach to Valence-Arousal Ratings of Words from Word-PPT.pdf

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[1] , "A Regression Approach to Valence-Arousal Ratings of Words from Word", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1268. Accessed: May. 25, 2017.
@article{1268-16,
url = {http://sigport.org/1268},
author = { },
publisher = {IEEE SigPort},
title = {A Regression Approach to Valence-Arousal Ratings of Words from Word},
year = {2016} }
TY - EJOUR
T1 - A Regression Approach to Valence-Arousal Ratings of Words from Word
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1268
ER -
. (2016). A Regression Approach to Valence-Arousal Ratings of Words from Word. IEEE SigPort. http://sigport.org/1268
, 2016. A Regression Approach to Valence-Arousal Ratings of Words from Word. Available at: http://sigport.org/1268.
. (2016). "A Regression Approach to Valence-Arousal Ratings of Words from Word." Web.
1. . A Regression Approach to Valence-Arousal Ratings of Words from Word [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1268

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