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Adaptive Array Signal Processing

Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins


A new method for designing single/multiple unimodular waveforms with good weighted correlation properties, which is

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1 March 2017 - 6:24pm
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ICASSP2017PosterLiVorobyov.pdf

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[1] , "Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1566. Accessed: Aug. 19, 2017.
@article{1566-17,
url = {http://sigport.org/1566},
author = { },
publisher = {IEEE SigPort},
title = {Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins},
year = {2017} }
TY - EJOUR
T1 - Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1566
ER -
. (2017). Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins. IEEE SigPort. http://sigport.org/1566
, 2017. Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins. Available at: http://sigport.org/1566.
. (2017). "Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins." Web.
1. . Efficient Single/Multiple Unimodular Waveform Design With Low Weighted Correlatioins [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1566

Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision


This work investigates the parameter estimation performance of super-resolution line spectral estimation using atomic norm minimization. The focus is on analyzing the algorithm's accuracy of inferring the frequencies and complex magnitudes from noisy observations. When the Signal-to-Noise Ratio is reasonably high and the true frequencies are separated by $O(\frac{1}{n})$, the atomic norm estimator is shown to localize the correct number of frequencies, each within a neighborhood of size $O(\sqrt{\frac{\log n}{n^3}} \sigma)$ of one of the true frequencies.

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10 December 2016 - 3:39pm
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Slides_GlobalSIP.pdf

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[1] , "Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1383. Accessed: Aug. 19, 2017.
@article{1383-16,
url = {http://sigport.org/1383},
author = { },
publisher = {IEEE SigPort},
title = {Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision},
year = {2016} }
TY - EJOUR
T1 - Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1383
ER -
. (2016). Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision. IEEE SigPort. http://sigport.org/1383
, 2016. Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision. Available at: http://sigport.org/1383.
. (2016). "Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision." Web.
1. . Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1383

Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision


This work investigates the parameter estimation performance of super-resolution line spectral estimation using atomic norm minimization. The focus is on analyzing the algorithm's accuracy of inferring the frequencies and complex magnitudes from noisy observations. When the Signal-to-Noise Ratio is reasonably high and the true frequencies are separated by $O(\frac{1}{n})$, the atomic norm estimator is shown to localize the correct number of frequencies, each within a neighborhood of size $O(\sqrt{\frac{\log n}{n^3}} \sigma)$ of one of the true frequencies.

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10 December 2016 - 3:38pm
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Slides_GlobalSIP.pdf

(97 downloads)

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[1] , "Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1382. Accessed: Aug. 19, 2017.
@article{1382-16,
url = {http://sigport.org/1382},
author = { },
publisher = {IEEE SigPort},
title = {Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision},
year = {2016} }
TY - EJOUR
T1 - Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1382
ER -
. (2016). Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision. IEEE SigPort. http://sigport.org/1382
, 2016. Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision. Available at: http://sigport.org/1382.
. (2016). "Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision." Web.
1. . Approximate Support Recovery of Atomic Line Spectral Estimation: A Tale of Resolution and Precision [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1382

Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement

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Authors:
Qing Shen, Wei Liu, Wei Cui, Siliang Wu
Submitted On:
19 March 2016 - 6:09am
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ICASSP2016.pdf

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[1] Qing Shen, Wei Liu, Wei Cui, Siliang Wu, "Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/798. Accessed: Aug. 19, 2017.
@article{798-16,
url = {http://sigport.org/798},
author = {Qing Shen; Wei Liu; Wei Cui; Siliang Wu },
publisher = {IEEE SigPort},
title = {Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement},
year = {2016} }
TY - EJOUR
T1 - Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement
AU - Qing Shen; Wei Liu; Wei Cui; Siliang Wu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/798
ER -
Qing Shen, Wei Liu, Wei Cui, Siliang Wu. (2016). Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement. IEEE SigPort. http://sigport.org/798
Qing Shen, Wei Liu, Wei Cui, Siliang Wu, 2016. Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement. Available at: http://sigport.org/798.
Qing Shen, Wei Liu, Wei Cui, Siliang Wu. (2016). "Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement." Web.
1. Qing Shen, Wei Liu, Wei Cui, Siliang Wu. Extension of Nested Arrays with the Fourth-Order Difference Co-Array Enhancement [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/798