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Signal and System Modeling, Representation and Estimation

Filtering out time-frequency areas using Gabor multipliers


We address the problem of filtering out localized time-frequency components in signals. The problem is formulatedas a minimization of a suitable quadratic form, that involves adata fidelity term on the short-time Fourier transform outsidethe support of the undesired component, and an energy pe-nalization term inside the support. The minimization yields alinear system whose solution can be expressed in closed formusing Gabor multipliers.

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5 June 2020 - 6:56am
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[1] , "Filtering out time-frequency areas using Gabor multipliers", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5455. Accessed: Jul. 04, 2020.
@article{5455-20,
url = {http://sigport.org/5455},
author = { },
publisher = {IEEE SigPort},
title = {Filtering out time-frequency areas using Gabor multipliers},
year = {2020} }
TY - EJOUR
T1 - Filtering out time-frequency areas using Gabor multipliers
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5455
ER -
. (2020). Filtering out time-frequency areas using Gabor multipliers. IEEE SigPort. http://sigport.org/5455
, 2020. Filtering out time-frequency areas using Gabor multipliers. Available at: http://sigport.org/5455.
. (2020). "Filtering out time-frequency areas using Gabor multipliers." Web.
1. . Filtering out time-frequency areas using Gabor multipliers [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5455

Conditional Density Driven Grid Design in Point-Mass Filter

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19 May 2020 - 8:27am
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[1] , "Conditional Density Driven Grid Design in Point-Mass Filter", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5400. Accessed: Jul. 04, 2020.
@article{5400-20,
url = {http://sigport.org/5400},
author = { },
publisher = {IEEE SigPort},
title = {Conditional Density Driven Grid Design in Point-Mass Filter},
year = {2020} }
TY - EJOUR
T1 - Conditional Density Driven Grid Design in Point-Mass Filter
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5400
ER -
. (2020). Conditional Density Driven Grid Design in Point-Mass Filter. IEEE SigPort. http://sigport.org/5400
, 2020. Conditional Density Driven Grid Design in Point-Mass Filter. Available at: http://sigport.org/5400.
. (2020). "Conditional Density Driven Grid Design in Point-Mass Filter." Web.
1. . Conditional Density Driven Grid Design in Point-Mass Filter [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5400

PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting


Many signal processing methods break the target signal into overlapping patches, process them separately, and then stitch them back to produce an output. How to merge the resulting patches at the overlaps is central to such methods. We propose a novel framework for this type of problem based on the idea that estimated patches should coincide at the overlaps (consensus), and develop an algorithm for solving the general problem. In particular, an efficient method for projecting patches onto the consensus constraint is presented.

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Ignacio Ramirez, Ignacio Hounie
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14 May 2020 - 10:07am
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[1] Ignacio Ramirez, Ignacio Hounie, "PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5300. Accessed: Jul. 04, 2020.
@article{5300-20,
url = {http://sigport.org/5300},
author = {Ignacio Ramirez; Ignacio Hounie },
publisher = {IEEE SigPort},
title = {PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting},
year = {2020} }
TY - EJOUR
T1 - PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting
AU - Ignacio Ramirez; Ignacio Hounie
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5300
ER -
Ignacio Ramirez, Ignacio Hounie. (2020). PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting. IEEE SigPort. http://sigport.org/5300
Ignacio Ramirez, Ignacio Hounie, 2020. PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting. Available at: http://sigport.org/5300.
Ignacio Ramirez, Ignacio Hounie. (2020). "PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting." Web.
1. Ignacio Ramirez, Ignacio Hounie. PACO and PCO-DCT: Patch Consensus and Its Application To Inpainting [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5300

State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations


This paper is concerned with the estimation of unknown drift functions of stochastic differential equations (SDEs) from observations of their sample paths. We propose to formulate this as a non-parametric Gaussian process regression problem and use an Itô-Taylor expansion for approximating the SDE. To address the computational complexity problem of Gaussian process regression, we cast the model in an equivalent state-space representation, such that (non-linear) Kalman filters and smoothers can be used.

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Authors:
Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä
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14 May 2020 - 8:09am
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[1] Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä, "State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5292. Accessed: Jul. 04, 2020.
@article{5292-20,
url = {http://sigport.org/5292},
author = {Zheng Zhao; Filip Tronarp; Roland Hostettler; and Simo Särkkä },
publisher = {IEEE SigPort},
title = {State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations},
year = {2020} }
TY - EJOUR
T1 - State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations
AU - Zheng Zhao; Filip Tronarp; Roland Hostettler; and Simo Särkkä
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5292
ER -
Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä. (2020). State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations. IEEE SigPort. http://sigport.org/5292
Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä, 2020. State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations. Available at: http://sigport.org/5292.
Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä. (2020). "State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations." Web.
1. Zheng Zhao, Filip Tronarp, Roland Hostettler, and Simo Särkkä. State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5292

Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO


In this paper, we present a new performance bound for uplink channel estimation (CE) accuracy in the Massive Multiple Input Multiple Output (MIMO) system. The proposed approach is based on noise power calculation after the CE unit in a multi-antenna receiver. Each time the impulse response of ideal channel estimation is decomposed into separate taps (beams) and cross-covariance matrix is calculated between them.

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Authors:
Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky
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14 May 2020 - 5:26am
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[1] Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky, "Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5276. Accessed: Jul. 04, 2020.
@article{5276-20,
url = {http://sigport.org/5276},
author = {Alexander Osinsky; Andrey Ivanov; Dmitry Yarotsky },
publisher = {IEEE SigPort},
title = {Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO},
year = {2020} }
TY - EJOUR
T1 - Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO
AU - Alexander Osinsky; Andrey Ivanov; Dmitry Yarotsky
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5276
ER -
Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky. (2020). Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO. IEEE SigPort. http://sigport.org/5276
Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky, 2020. Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO. Available at: http://sigport.org/5276.
Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky. (2020). "Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO." Web.
1. Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky. Theoretical Performance Bound of Uplink Channel Estimation Accuracy in Massive MIMO [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5276

Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study


In this paper we investigate the problem of time of arrival estimation which occurs in many real-world applications, such as indoor localization or non-destructive testing via ultrasound or radar. A problem that is often overlooked when analyzing these systems is that in practice, we will typically not have exact information about the pulse shape. Therefore, there may be a mismatch between the parametric model that is assumed to derive and study the estimators versus the real model we find in practice.

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14 May 2020 - 4:25am
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[1] , "Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5263. Accessed: Jul. 04, 2020.
@article{5263-20,
url = {http://sigport.org/5263},
author = { },
publisher = {IEEE SigPort},
title = {Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study},
year = {2020} }
TY - EJOUR
T1 - Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5263
ER -
. (2020). Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study. IEEE SigPort. http://sigport.org/5263
, 2020. Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study. Available at: http://sigport.org/5263.
. (2020). "Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study." Web.
1. . Misspecified Cramer-Rao Bound For Delay Estimation With A Mismatched Waveform: A Case Study [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5263

EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS


The problem of row-sparse signal reconstruction for complex-valued data with outliers is investigated in this paper. First, we formulate the problem by taking advantage of a sparse weight matrix, which is used to down-weight the outliers. The formulated problem belongs to LASSO-type problems, and such problems can be efficiently solved via cyclic coordinate descent (CCD). We propose an extended CCD algorithm to solve the problem for complex-valued measurements, which requires careful characterization and derivation.

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Authors:
Huiping Huang, Hing Cheung So, Abdelhak M. Zoubir
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14 May 2020 - 3:52am
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[1] Huiping Huang, Hing Cheung So, Abdelhak M. Zoubir, "EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5258. Accessed: Jul. 04, 2020.
@article{5258-20,
url = {http://sigport.org/5258},
author = {Huiping Huang; Hing Cheung So; Abdelhak M. Zoubir },
publisher = {IEEE SigPort},
title = {EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS},
year = {2020} }
TY - EJOUR
T1 - EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS
AU - Huiping Huang; Hing Cheung So; Abdelhak M. Zoubir
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5258
ER -
Huiping Huang, Hing Cheung So, Abdelhak M. Zoubir. (2020). EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS. IEEE SigPort. http://sigport.org/5258
Huiping Huang, Hing Cheung So, Abdelhak M. Zoubir, 2020. EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS. Available at: http://sigport.org/5258.
Huiping Huang, Hing Cheung So, Abdelhak M. Zoubir. (2020). "EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS." Web.
1. Huiping Huang, Hing Cheung So, Abdelhak M. Zoubir. EXTENDED CYCLIC COORDINATE DESCENT FOR ROBUST ROW-SPARSE SIGNAL RECONSTRUCTION IN THE PRESENCE OF OUTLIERS [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5258

Regularized partial phase synchrony index applied to dynamical functional connectivity estimation


We study the inference of conditional independence graph from the partial Phase Locking Value (PLV) index of multivariate time series. A typical application is the inference of temporal functional connectivity from brain data. We extend the recently proposed time-varying graphical lasso to the measurement of partial locking values, yielding a sparse and temporally coherent dynamical graph that characterizes the evolution of the phase synchrony between each pair of signals.

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Gaëtan Frusque, Julien Jung, Pierre Borgnat, Paulo Gonçalves
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14 May 2020 - 3:46am
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[1] Gaëtan Frusque, Julien Jung, Pierre Borgnat, Paulo Gonçalves, "Regularized partial phase synchrony index applied to dynamical functional connectivity estimation", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5257. Accessed: Jul. 04, 2020.
@article{5257-20,
url = {http://sigport.org/5257},
author = {Gaëtan Frusque; Julien Jung; Pierre Borgnat; Paulo Gonçalves },
publisher = {IEEE SigPort},
title = {Regularized partial phase synchrony index applied to dynamical functional connectivity estimation},
year = {2020} }
TY - EJOUR
T1 - Regularized partial phase synchrony index applied to dynamical functional connectivity estimation
AU - Gaëtan Frusque; Julien Jung; Pierre Borgnat; Paulo Gonçalves
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5257
ER -
Gaëtan Frusque, Julien Jung, Pierre Borgnat, Paulo Gonçalves. (2020). Regularized partial phase synchrony index applied to dynamical functional connectivity estimation. IEEE SigPort. http://sigport.org/5257
Gaëtan Frusque, Julien Jung, Pierre Borgnat, Paulo Gonçalves, 2020. Regularized partial phase synchrony index applied to dynamical functional connectivity estimation. Available at: http://sigport.org/5257.
Gaëtan Frusque, Julien Jung, Pierre Borgnat, Paulo Gonçalves. (2020). "Regularized partial phase synchrony index applied to dynamical functional connectivity estimation." Web.
1. Gaëtan Frusque, Julien Jung, Pierre Borgnat, Paulo Gonçalves. Regularized partial phase synchrony index applied to dynamical functional connectivity estimation [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5257

Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective

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Holger Boche, Ullrich Mönich
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14 May 2020 - 3:35am
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[1] Holger Boche, Ullrich Mönich, "Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5254. Accessed: Jul. 04, 2020.
@article{5254-20,
url = {http://sigport.org/5254},
author = {Holger Boche; Ullrich Mönich },
publisher = {IEEE SigPort},
title = {Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective},
year = {2020} }
TY - EJOUR
T1 - Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective
AU - Holger Boche; Ullrich Mönich
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5254
ER -
Holger Boche, Ullrich Mönich. (2020). Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective. IEEE SigPort. http://sigport.org/5254
Holger Boche, Ullrich Mönich, 2020. Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective. Available at: http://sigport.org/5254.
Holger Boche, Ullrich Mönich. (2020). "Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective." Web.
1. Holger Boche, Ullrich Mönich. Optimal Sampling Rate and Bandwidth of Bandlimited Signals - An Algorithmic Perspective [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5254

Estimating Centrality Blindly from Low-pass Filtered Graph Signals


This work considers blind methods for centrality estimation from graph signals. We model graph signals as the outcome of an unknown
low-pass graph filter excited with influences governed by a sparse sub-graph. This model is compatible with a number of data
generation process on graphs, including stock data and opinion dynamics. Based on the said graph signal model, we first prove that the

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13 May 2020 - 11:04pm
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[1] , "Estimating Centrality Blindly from Low-pass Filtered Graph Signals", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5212. Accessed: Jul. 04, 2020.
@article{5212-20,
url = {http://sigport.org/5212},
author = { },
publisher = {IEEE SigPort},
title = {Estimating Centrality Blindly from Low-pass Filtered Graph Signals},
year = {2020} }
TY - EJOUR
T1 - Estimating Centrality Blindly from Low-pass Filtered Graph Signals
AU -
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5212
ER -
. (2020). Estimating Centrality Blindly from Low-pass Filtered Graph Signals. IEEE SigPort. http://sigport.org/5212
, 2020. Estimating Centrality Blindly from Low-pass Filtered Graph Signals. Available at: http://sigport.org/5212.
. (2020). "Estimating Centrality Blindly from Low-pass Filtered Graph Signals." Web.
1. . Estimating Centrality Blindly from Low-pass Filtered Graph Signals [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5212

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