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Statistical Signal Processing

Dirichlet process mixture models for time-dependent clustering


In many problems of signal processing, an important task is the classification of data. A group of methods that has attracted much interest for this purpose are the nonparametric Bayesian methods, and in particular, those based on the Dirichlet process. A useful metaphor for various generalizations of the Dirichlet process has been the Chinese restaurant process. Often the task of classification must be carried out in a sequential manner, and to that end the concepts from Bayesian non-parametrics cannot be applied straightforwardly.

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Authors:
Kezi Yu, Petar M. Djuric
Submitted On:
16 March 2016 - 2:05pm
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[1] Kezi Yu, Petar M. Djuric, "Dirichlet process mixture models for time-dependent clustering", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/722. Accessed: Jul. 20, 2019.
@article{722-16,
url = {http://sigport.org/722},
author = {Kezi Yu; Petar M. Djuric },
publisher = {IEEE SigPort},
title = {Dirichlet process mixture models for time-dependent clustering},
year = {2016} }
TY - EJOUR
T1 - Dirichlet process mixture models for time-dependent clustering
AU - Kezi Yu; Petar M. Djuric
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/722
ER -
Kezi Yu, Petar M. Djuric. (2016). Dirichlet process mixture models for time-dependent clustering. IEEE SigPort. http://sigport.org/722
Kezi Yu, Petar M. Djuric, 2016. Dirichlet process mixture models for time-dependent clustering. Available at: http://sigport.org/722.
Kezi Yu, Petar M. Djuric. (2016). "Dirichlet process mixture models for time-dependent clustering." Web.
1. Kezi Yu, Petar M. Djuric. Dirichlet process mixture models for time-dependent clustering [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/722

ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION

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Authors:
Mohammadreza Hassannejad Bibalan,Hamidreza Amindavar
Submitted On:
17 March 2016 - 9:08pm
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[1] Mohammadreza Hassannejad Bibalan,Hamidreza Amindavar, "ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/714. Accessed: Jul. 20, 2019.
@article{714-16,
url = {http://sigport.org/714},
author = {Mohammadreza Hassannejad Bibalan;Hamidreza Amindavar },
publisher = {IEEE SigPort},
title = {ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION},
year = {2016} }
TY - EJOUR
T1 - ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION
AU - Mohammadreza Hassannejad Bibalan;Hamidreza Amindavar
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/714
ER -
Mohammadreza Hassannejad Bibalan,Hamidreza Amindavar. (2016). ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION. IEEE SigPort. http://sigport.org/714
Mohammadreza Hassannejad Bibalan,Hamidreza Amindavar, 2016. ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION. Available at: http://sigport.org/714.
Mohammadreza Hassannejad Bibalan,Hamidreza Amindavar. (2016). "ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION." Web.
1. Mohammadreza Hassannejad Bibalan,Hamidreza Amindavar. ON PARAMETER ESTIMATION OF SYMMETRIC ALPHA-STABLE DISTRIBUTION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/714

Sequential Monte Carlo sampling for correlated latent long-memory time-series


We propose sequential Monte Carlo (SMC) methods for state-space models. The latent processes represent correlated mixtures of fractional Gaussian processes embedded in white Gaussian noises and the observed data are nonlinear functions of the latent states.

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Authors:
Iñigo Urteaga, Mónica F. Bugallo and Petar M. Djurić
Submitted On:
15 March 2016 - 4:45pm
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[1] Iñigo Urteaga, Mónica F. Bugallo and Petar M. Djurić, "Sequential Monte Carlo sampling for correlated latent long-memory time-series", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/697. Accessed: Jul. 20, 2019.
@article{697-16,
url = {http://sigport.org/697},
author = {Iñigo Urteaga; Mónica F. Bugallo and Petar M. Djurić },
publisher = {IEEE SigPort},
title = {Sequential Monte Carlo sampling for correlated latent long-memory time-series},
year = {2016} }
TY - EJOUR
T1 - Sequential Monte Carlo sampling for correlated latent long-memory time-series
AU - Iñigo Urteaga; Mónica F. Bugallo and Petar M. Djurić
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/697
ER -
Iñigo Urteaga, Mónica F. Bugallo and Petar M. Djurić. (2016). Sequential Monte Carlo sampling for correlated latent long-memory time-series. IEEE SigPort. http://sigport.org/697
Iñigo Urteaga, Mónica F. Bugallo and Petar M. Djurić, 2016. Sequential Monte Carlo sampling for correlated latent long-memory time-series. Available at: http://sigport.org/697.
Iñigo Urteaga, Mónica F. Bugallo and Petar M. Djurić. (2016). "Sequential Monte Carlo sampling for correlated latent long-memory time-series." Web.
1. Iñigo Urteaga, Mónica F. Bugallo and Petar M. Djurić. Sequential Monte Carlo sampling for correlated latent long-memory time-series [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/697

Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio

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Authors:
Aaron Pries, David Ramirez, Peter J. Schreier
Submitted On:
14 March 2016 - 9:41am
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[1] Aaron Pries, David Ramirez, Peter J. Schreier, "Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/673. Accessed: Jul. 20, 2019.
@article{673-16,
url = {http://sigport.org/673},
author = {Aaron Pries; David Ramirez; Peter J. Schreier },
publisher = {IEEE SigPort},
title = {Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio},
year = {2016} }
TY - EJOUR
T1 - Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio
AU - Aaron Pries; David Ramirez; Peter J. Schreier
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/673
ER -
Aaron Pries, David Ramirez, Peter J. Schreier. (2016). Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio. IEEE SigPort. http://sigport.org/673
Aaron Pries, David Ramirez, Peter J. Schreier, 2016. Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio. Available at: http://sigport.org/673.
Aaron Pries, David Ramirez, Peter J. Schreier. (2016). "Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio." Web.
1. Aaron Pries, David Ramirez, Peter J. Schreier. Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/673

STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION


Atmospheric conditions are known to affect the Received Sig- nal Level (RSL) in commercial microwave links (MWLs), that operate at frequencies of tens of GHz. Study of these ef- fects is of great importance both for communication engineers and for environmental monitoring. In this paper we study the phenomenon of a wet antenna. During periods of high rela- tive humidity (RH), a thin layer of water may collect on the outside cover of the microwave units, resulting in increased signal attenuation. Here, we focus on the estimation of the signal power loss caused due to this phenomenon.

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Authors:
Naom David, Oz Harel, Pinhas Alpert, Hagit Messer
Submitted On:
14 March 2016 - 12:46am
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[1] Naom David, Oz Harel, Pinhas Alpert, Hagit Messer, " STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/658. Accessed: Jul. 20, 2019.
@article{658-16,
url = {http://sigport.org/658},
author = {Naom David; Oz Harel; Pinhas Alpert; Hagit Messer },
publisher = {IEEE SigPort},
title = { STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION},
year = {2016} }
TY - EJOUR
T1 - STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION
AU - Naom David; Oz Harel; Pinhas Alpert; Hagit Messer
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/658
ER -
Naom David, Oz Harel, Pinhas Alpert, Hagit Messer. (2016). STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION. IEEE SigPort. http://sigport.org/658
Naom David, Oz Harel, Pinhas Alpert, Hagit Messer, 2016. STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION. Available at: http://sigport.org/658.
Naom David, Oz Harel, Pinhas Alpert, Hagit Messer. (2016). " STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION." Web.
1. Naom David, Oz Harel, Pinhas Alpert, Hagit Messer. STUDY OF ATTENUATION DUE TO WET ANTENNA IN MICROWAVE RADIO COMMUNICATION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/658

Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels


2-sphere wireframe as an orthogonal projection

In many estimation problems of interest the unknown parameters reside on spherical manifolds. As most common filtering algorithms assume that parameters have Gaussian prior distributions, their application to such problems leads to suboptimal performance. In this letter, we propose a model in which the unknown unit-norm parameter vectors have Fisher-Bingham (F-B) prior distributions.

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Authors:
Marcelo G. S. Bruno
Submitted On:
12 March 2016 - 10:39am
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[1] Marcelo G. S. Bruno, "Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/644. Accessed: Jul. 20, 2019.
@article{644-16,
url = {http://sigport.org/644},
author = {Marcelo G. S. Bruno },
publisher = {IEEE SigPort},
title = {Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels},
year = {2016} }
TY - EJOUR
T1 - Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels
AU - Marcelo G. S. Bruno
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/644
ER -
Marcelo G. S. Bruno. (2016). Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels. IEEE SigPort. http://sigport.org/644
Marcelo G. S. Bruno, 2016. Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels. Available at: http://sigport.org/644.
Marcelo G. S. Bruno. (2016). "Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels." Web.
1. Marcelo G. S. Bruno. Sequential Bayesian Algorithms for Identification and Blind Equalization of Unit-Norm Channels [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/644

Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information


We consider an oligopoly dynamic pricing problem where the demand model is unknown and the sellers have different marginal costs. We formulate the problem as a repeated game with incomplete information. We develop a dynamic pricing strategy that leads to a Pareto-efficient and subgame-perfect equilibrium and offers a bounded regret over an infinite horizon, where regret is defined as the expected cumulative profit loss as compared to the ideal scenario with a known demand model.

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19 March 2016 - 9:33pm
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[1] , "Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/626. Accessed: Jul. 20, 2019.
@article{626-16,
url = {http://sigport.org/626},
author = { },
publisher = {IEEE SigPort},
title = {Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information},
year = {2016} }
TY - EJOUR
T1 - Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/626
ER -
. (2016). Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information. IEEE SigPort. http://sigport.org/626
, 2016. Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information. Available at: http://sigport.org/626.
. (2016). "Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information." Web.
1. . Oligopoly Dynamic Pricing: A Repeated Game with Incomplete Information [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/626

Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation


Biased estimators can outperform unbiased ones in terms of the mean square error (MSE). In this work we treat all estimators in the Bayesian framework, where the best linear unbiased estimator (BLUE) fulfills the so called global conditional unbiased constraint. Recently, component-wise conditionally unbiased linear minimum mean square error (CWCU LMMSE) estimators have been introduced.

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Authors:
Oliver Lang, Christian Hofbauer
Submitted On:
23 February 2016 - 1:44pm
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[1] Oliver Lang, Christian Hofbauer, "Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/599. Accessed: Jul. 20, 2019.
@article{599-16,
url = {http://sigport.org/599},
author = {Oliver Lang; Christian Hofbauer },
publisher = {IEEE SigPort},
title = {Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation},
year = {2016} }
TY - EJOUR
T1 - Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation
AU - Oliver Lang; Christian Hofbauer
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/599
ER -
Oliver Lang, Christian Hofbauer. (2016). Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation. IEEE SigPort. http://sigport.org/599
Oliver Lang, Christian Hofbauer, 2016. Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation. Available at: http://sigport.org/599.
Oliver Lang, Christian Hofbauer. (2016). "Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation." Web.
1. Oliver Lang, Christian Hofbauer. Component-Wise Conditionally Unbiased Widely Linear MMSE Estimation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/599

On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization


Cooperative localization plays a key role in location aware service of wireless networks. However, the statistical-based estimator of network localization, e.g., the maximum likelihood estimator (MLE) or the maximum a posterior (MAP) estimator, is commonly non-convex due to the nonlinear measurement function and/or the non-Gaussian disturbance, which complicates the localization of network nodes. In this paper, a novel particleassisted

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Authors:
Bingpeng Zhou
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23 February 2016 - 1:44pm
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[1] Bingpeng Zhou, "On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/533. Accessed: Jul. 20, 2019.
@article{533-15,
url = {http://sigport.org/533},
author = {Bingpeng Zhou },
publisher = {IEEE SigPort},
title = {On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization},
year = {2015} }
TY - EJOUR
T1 - On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization
AU - Bingpeng Zhou
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/533
ER -
Bingpeng Zhou. (2015). On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization. IEEE SigPort. http://sigport.org/533
Bingpeng Zhou, 2015. On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization. Available at: http://sigport.org/533.
Bingpeng Zhou. (2015). "On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization." Web.
1. Bingpeng Zhou. On the Particle-Assisted Stochastic Search in Cooperative Wireless Network Localization [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/533

Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach


An extended version of the paper has been submitted to IEEE Transactions on Signal Processing (TSP):
B. Mamandipoor, D. Ramasamy, U. Madhow, “Newtonized Orthogonal Matching Pursuit: Frequency Estimation over the Continuum,”arXiv preprint arXiv:1509.01942, 2015.

A MATLAB implementation of the algorithm can be found here:
https://bitbucket.org/wcslspectralestimation/continuous-frequency-estima...

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Authors:
Dinesh Ramasamy, Upamanyu Madhow
Submitted On:
23 February 2016 - 1:44pm
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[1] Dinesh Ramasamy, Upamanyu Madhow, "Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/471. Accessed: Jul. 20, 2019.
@article{471-15,
url = {http://sigport.org/471},
author = {Dinesh Ramasamy; Upamanyu Madhow },
publisher = {IEEE SigPort},
title = {Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach},
year = {2015} }
TY - EJOUR
T1 - Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach
AU - Dinesh Ramasamy; Upamanyu Madhow
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/471
ER -
Dinesh Ramasamy, Upamanyu Madhow. (2015). Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach. IEEE SigPort. http://sigport.org/471
Dinesh Ramasamy, Upamanyu Madhow, 2015. Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach. Available at: http://sigport.org/471.
Dinesh Ramasamy, Upamanyu Madhow. (2015). "Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach." Web.
1. Dinesh Ramasamy, Upamanyu Madhow. Frequency Estimation for a Mixture of Sinusoids: A Near-Optimal Sequential Approach [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/471

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