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ICASSP 2018

ICASSP is the world's largest and most comprehensive technical conference on signal processing and its applications. It provides a fantastic networking opportunity for like-minded professionals from around the world. ICASSP 2018 conference will feature world-class presentations by internationally renowned speakers and cutting-edge session topics. Visit ICASSP 2018.

Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects


In this work, we consider the task of acoustic and articulatory feature based automatic classification of Amyotrophic Lateral Sclerosis (ALS) patients and healthy subjects using speech tasks. In particular, we compare the roles of different types of speech tasks, namely rehearsed speech, spontaneous speech and repeated words for this purpose. Simultaneous articulatory and speech data were recorded from 8 healthy controls and 8 ALS patients using AG501 for the classification experiments.

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Authors:
Deep Patel, BK Yaminiy, Meera SSy, Shivashankar Ny, Preethish-Kumar Veeramaniz, Seena Vengalilz, Kiran Polavarapuz, Saraswati Nashiz, Atchayaram Naliniz, Prasanta Kumar Ghosh
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24 April 2018 - 1:18am
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ICASSP_Final_April21.pdf

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[1] Deep Patel, BK Yaminiy, Meera SSy, Shivashankar Ny, Preethish-Kumar Veeramaniz, Seena Vengalilz, Kiran Polavarapuz, Saraswati Nashiz, Atchayaram Naliniz, Prasanta Kumar Ghosh, "Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3158. Accessed: Sep. 18, 2018.
@article{3158-18,
url = {http://sigport.org/3158},
author = {Deep Patel; BK Yaminiy; Meera SSy; Shivashankar Ny; Preethish-Kumar Veeramaniz; Seena Vengalilz; Kiran Polavarapuz; Saraswati Nashiz; Atchayaram Naliniz; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects},
year = {2018} }
TY - EJOUR
T1 - Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects
AU - Deep Patel; BK Yaminiy; Meera SSy; Shivashankar Ny; Preethish-Kumar Veeramaniz; Seena Vengalilz; Kiran Polavarapuz; Saraswati Nashiz; Atchayaram Naliniz; Prasanta Kumar Ghosh
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3158
ER -
Deep Patel, BK Yaminiy, Meera SSy, Shivashankar Ny, Preethish-Kumar Veeramaniz, Seena Vengalilz, Kiran Polavarapuz, Saraswati Nashiz, Atchayaram Naliniz, Prasanta Kumar Ghosh. (2018). Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects. IEEE SigPort. http://sigport.org/3158
Deep Patel, BK Yaminiy, Meera SSy, Shivashankar Ny, Preethish-Kumar Veeramaniz, Seena Vengalilz, Kiran Polavarapuz, Saraswati Nashiz, Atchayaram Naliniz, Prasanta Kumar Ghosh, 2018. Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects. Available at: http://sigport.org/3158.
Deep Patel, BK Yaminiy, Meera SSy, Shivashankar Ny, Preethish-Kumar Veeramaniz, Seena Vengalilz, Kiran Polavarapuz, Saraswati Nashiz, Atchayaram Naliniz, Prasanta Kumar Ghosh. (2018). "Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects." Web.
1. Deep Patel, BK Yaminiy, Meera SSy, Shivashankar Ny, Preethish-Kumar Veeramaniz, Seena Vengalilz, Kiran Polavarapuz, Saraswati Nashiz, Atchayaram Naliniz, Prasanta Kumar Ghosh. Comparison of speech tasks for automatic classification of patients with amyotrophic lateral sclerosis and healthy subjects [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3158

INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING


We measure the effect of small amounts of systematic and
random label noise caused by slightly misaligned ground truth
labels in a fine grained audio signal labeling task. The task
we choose to demonstrate these effects on is also known as
framewise polyphonic transcription or note quantized multi-
f0 estimation, and transforms a monaural audio signal into a
sequence of note indicator labels. It will be shown that even
slight misalignments have clearly apparent effects, demonstrating a great sensitivity of convolutional neural networks

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23 April 2018 - 9:01pm
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[1] , "INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3156. Accessed: Sep. 18, 2018.
@article{3156-18,
url = {http://sigport.org/3156},
author = { },
publisher = {IEEE SigPort},
title = {INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING},
year = {2018} }
TY - EJOUR
T1 - INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3156
ER -
. (2018). INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING. IEEE SigPort. http://sigport.org/3156
, 2018. INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING. Available at: http://sigport.org/3156.
. (2018). "INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING." Web.
1. . INVESTIGATING LABEL NOISE SENSITIVITY OF CONVOLUTIONAL NEURAL NETWORKS FOR FINE GRAINED AUDIO SIGNAL LABELLING [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3156

AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO

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Authors:
Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu
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23 April 2018 - 8:52pm
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[1] Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu, "AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3155. Accessed: Sep. 18, 2018.
@article{3155-18,
url = {http://sigport.org/3155},
author = {Alistair Letcher; Jelena Trišović; Collin Cademartori; Xi Chen; Jason Xu },
publisher = {IEEE SigPort},
title = {AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO},
year = {2018} }
TY - EJOUR
T1 - AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO
AU - Alistair Letcher; Jelena Trišović; Collin Cademartori; Xi Chen; Jason Xu
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3155
ER -
Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu. (2018). AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO. IEEE SigPort. http://sigport.org/3155
Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu, 2018. AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO. Available at: http://sigport.org/3155.
Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu. (2018). "AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO." Web.
1. Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu. AUTOMATIC CONFLICT DETECTION IN POLICE BODY-WORN AUDIO [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3155

MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL

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Authors:
Bo Li, Tara Sainath, Khe Chai Sim, Michiel Bacchiani, Eugene Weinstein, Patrick Nguyen, Zhifeng Chen, Yonghui Wu, Kanishka Rao
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23 April 2018 - 7:59pm
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MultiDialect LAS

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[1] Bo Li, Tara Sainath, Khe Chai Sim, Michiel Bacchiani, Eugene Weinstein, Patrick Nguyen, Zhifeng Chen, Yonghui Wu, Kanishka Rao, "MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3154. Accessed: Sep. 18, 2018.
@article{3154-18,
url = {http://sigport.org/3154},
author = {Bo Li; Tara Sainath; Khe Chai Sim; Michiel Bacchiani; Eugene Weinstein; Patrick Nguyen; Zhifeng Chen; Yonghui Wu; Kanishka Rao },
publisher = {IEEE SigPort},
title = {MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL},
year = {2018} }
TY - EJOUR
T1 - MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL
AU - Bo Li; Tara Sainath; Khe Chai Sim; Michiel Bacchiani; Eugene Weinstein; Patrick Nguyen; Zhifeng Chen; Yonghui Wu; Kanishka Rao
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3154
ER -
Bo Li, Tara Sainath, Khe Chai Sim, Michiel Bacchiani, Eugene Weinstein, Patrick Nguyen, Zhifeng Chen, Yonghui Wu, Kanishka Rao. (2018). MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL. IEEE SigPort. http://sigport.org/3154
Bo Li, Tara Sainath, Khe Chai Sim, Michiel Bacchiani, Eugene Weinstein, Patrick Nguyen, Zhifeng Chen, Yonghui Wu, Kanishka Rao, 2018. MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL. Available at: http://sigport.org/3154.
Bo Li, Tara Sainath, Khe Chai Sim, Michiel Bacchiani, Eugene Weinstein, Patrick Nguyen, Zhifeng Chen, Yonghui Wu, Kanishka Rao. (2018). "MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL." Web.
1. Bo Li, Tara Sainath, Khe Chai Sim, Michiel Bacchiani, Eugene Weinstein, Patrick Nguyen, Zhifeng Chen, Yonghui Wu, Kanishka Rao. MULTI-DIALECT SPEECH RECOGNITION WITH A SINGLE SEQUENCE-TO-SEQUENCE MODEL [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3154

Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization


This paper proposes an extension of multichannel non-negative matrix factorization (MNMF) that simultaneously solves source separation and dereverberation. While MNMF was originally formulated under an underdetermined problem setting where sources outnumber microphones, a determined counterpart of MNMF, which we call the determined MNMF (DMNMF), has recently been proposed with notable success.

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Authors:
Hideaki Kagami, Hirokazu Kameoka, Masahiro Yukawa
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23 April 2018 - 5:00pm
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Kagami2018ICASSP03.pdf

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[1] Hideaki Kagami, Hirokazu Kameoka, Masahiro Yukawa, "Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3153. Accessed: Sep. 18, 2018.
@article{3153-18,
url = {http://sigport.org/3153},
author = {Hideaki Kagami; Hirokazu Kameoka; Masahiro Yukawa },
publisher = {IEEE SigPort},
title = {Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization},
year = {2018} }
TY - EJOUR
T1 - Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization
AU - Hideaki Kagami; Hirokazu Kameoka; Masahiro Yukawa
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3153
ER -
Hideaki Kagami, Hirokazu Kameoka, Masahiro Yukawa. (2018). Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization. IEEE SigPort. http://sigport.org/3153
Hideaki Kagami, Hirokazu Kameoka, Masahiro Yukawa, 2018. Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization. Available at: http://sigport.org/3153.
Hideaki Kagami, Hirokazu Kameoka, Masahiro Yukawa. (2018). "Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization." Web.
1. Hideaki Kagami, Hirokazu Kameoka, Masahiro Yukawa. Joint Separation and Dereverberation of Reverberant Mixtures with Determined Multichannel Non-negative Matrix Factorization [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3153

Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update


Researchers have recently examined a modified approach to sparse coding that encourages dictionaries to learn anomalous features. This is done by incorporating the matrix 1-norm, or \ell_{1,\infty} mixed matrix norm, into the dictionary update portion of a sparse coding algorithm. However, solving a matrix norm minimization problem in each iteration of the algorithm

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Authors:
Bradley M Whitaker, David V Anderson
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23 April 2018 - 1:16pm
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[1] Bradley M Whitaker, David V Anderson, "Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3152. Accessed: Sep. 18, 2018.
@article{3152-18,
url = {http://sigport.org/3152},
author = {Bradley M Whitaker; David V Anderson },
publisher = {IEEE SigPort},
title = {Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update},
year = {2018} }
TY - EJOUR
T1 - Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update
AU - Bradley M Whitaker; David V Anderson
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3152
ER -
Bradley M Whitaker, David V Anderson. (2018). Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update. IEEE SigPort. http://sigport.org/3152
Bradley M Whitaker, David V Anderson, 2018. Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update. Available at: http://sigport.org/3152.
Bradley M Whitaker, David V Anderson. (2018). "Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update." Web.
1. Bradley M Whitaker, David V Anderson. Using Block Coordinate Descent to Learn Sparse Coding Dictionaries with a Matrix Norm Update [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3152

USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY

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Authors:
R. Soundar Raja James, K. Naik and A. Nayak
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23 April 2018 - 12:51pm
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[1] R. Soundar Raja James, K. Naik and A. Nayak, "USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3151. Accessed: Sep. 18, 2018.
@article{3151-18,
url = {http://sigport.org/3151},
author = {R. Soundar Raja James; K. Naik and A. Nayak },
publisher = {IEEE SigPort},
title = {USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY},
year = {2018} }
TY - EJOUR
T1 - USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY
AU - R. Soundar Raja James; K. Naik and A. Nayak
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3151
ER -
R. Soundar Raja James, K. Naik and A. Nayak. (2018). USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY. IEEE SigPort. http://sigport.org/3151
R. Soundar Raja James, K. Naik and A. Nayak, 2018. USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY. Available at: http://sigport.org/3151.
R. Soundar Raja James, K. Naik and A. Nayak. (2018). "USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY." Web.
1. R. Soundar Raja James, K. Naik and A. Nayak. USING DEEP LEARNING TO CLASSIFY POWER CONSUMPTION SIGNALS OF WIRELESS DEVICES: AN APPLICATION TO CYBERSECURITY [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3151

Low Rank Fourier Ptychography

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Authors:
Zhengyu Chen, Gauri Jagatap, Seyedehsara Nayer, Chinmay Hegde, Namrata Vaswani
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23 April 2018 - 11:43am
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[1] Zhengyu Chen, Gauri Jagatap, Seyedehsara Nayer, Chinmay Hegde, Namrata Vaswani, "Low Rank Fourier Ptychography", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3150. Accessed: Sep. 18, 2018.
@article{3150-18,
url = {http://sigport.org/3150},
author = {Zhengyu Chen; Gauri Jagatap; Seyedehsara Nayer; Chinmay Hegde; Namrata Vaswani },
publisher = {IEEE SigPort},
title = {Low Rank Fourier Ptychography},
year = {2018} }
TY - EJOUR
T1 - Low Rank Fourier Ptychography
AU - Zhengyu Chen; Gauri Jagatap; Seyedehsara Nayer; Chinmay Hegde; Namrata Vaswani
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3150
ER -
Zhengyu Chen, Gauri Jagatap, Seyedehsara Nayer, Chinmay Hegde, Namrata Vaswani. (2018). Low Rank Fourier Ptychography. IEEE SigPort. http://sigport.org/3150
Zhengyu Chen, Gauri Jagatap, Seyedehsara Nayer, Chinmay Hegde, Namrata Vaswani, 2018. Low Rank Fourier Ptychography. Available at: http://sigport.org/3150.
Zhengyu Chen, Gauri Jagatap, Seyedehsara Nayer, Chinmay Hegde, Namrata Vaswani. (2018). "Low Rank Fourier Ptychography." Web.
1. Zhengyu Chen, Gauri Jagatap, Seyedehsara Nayer, Chinmay Hegde, Namrata Vaswani. Low Rank Fourier Ptychography [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3150

ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES

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Authors:
Alihan Kaplan, Volker Pohl, Dae Gwan Lee
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24 April 2018 - 9:19am
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[1] Alihan Kaplan, Volker Pohl, Dae Gwan Lee, "ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3149. Accessed: Sep. 18, 2018.
@article{3149-18,
url = {http://sigport.org/3149},
author = {Alihan Kaplan; Volker Pohl; Dae Gwan Lee },
publisher = {IEEE SigPort},
title = {ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES},
year = {2018} }
TY - EJOUR
T1 - ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES
AU - Alihan Kaplan; Volker Pohl; Dae Gwan Lee
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3149
ER -
Alihan Kaplan, Volker Pohl, Dae Gwan Lee. (2018). ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES. IEEE SigPort. http://sigport.org/3149
Alihan Kaplan, Volker Pohl, Dae Gwan Lee, 2018. ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES. Available at: http://sigport.org/3149.
Alihan Kaplan, Volker Pohl, Dae Gwan Lee. (2018). "ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES." Web.
1. Alihan Kaplan, Volker Pohl, Dae Gwan Lee. ON COMPRESSIVE SENSING OF SPARSE COVARIANCE MATRICES USING DETERMINISTIC SENSING MATRICES [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3149

MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets

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Authors:
Steven Herbert, James Hopgood, Bernie Mulgrew
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23 April 2018 - 4:36am
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SJH_ICASSP_2018.pdf

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[1] Steven Herbert, James Hopgood, Bernie Mulgrew, " MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3147. Accessed: Sep. 18, 2018.
@article{3147-18,
url = {http://sigport.org/3147},
author = {Steven Herbert; James Hopgood; Bernie Mulgrew },
publisher = {IEEE SigPort},
title = { MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets},
year = {2018} }
TY - EJOUR
T1 - MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets
AU - Steven Herbert; James Hopgood; Bernie Mulgrew
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3147
ER -
Steven Herbert, James Hopgood, Bernie Mulgrew. (2018). MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets. IEEE SigPort. http://sigport.org/3147
Steven Herbert, James Hopgood, Bernie Mulgrew, 2018. MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets. Available at: http://sigport.org/3147.
Steven Herbert, James Hopgood, Bernie Mulgrew. (2018). " MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets." Web.
1. Steven Herbert, James Hopgood, Bernie Mulgrew. MMSE Adaptive Waveform Design for a MIMO Active Sensing System Tracking Multiple Moving Targets [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3147

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