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Applications of Sensor Array and Multi-channel Signal Processing

Sine-based EB-ESPRIT for source localization


The eigenbeam-ESPRIT (EB-ESPRIT) is well known as a high-resolution parametric direction-of-arrival (DOA) estimation technique for a spherical microphone array. Unlike other eigenbeam beamformers such as EB-MVDR and EB-MUSIC, there is no need for exhaustive grid-search with EB-ESPRIT. However, when sources are positioned near the equator, the EB-ESPRIT inevitably induces a singularity problem due to the singularity of its tangent function utilized as a directional parameter. Here, a new EB-ESPRIT technique based on a nonsingular directional parameter is proposed.

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Authors:
Byeongho Jo, Jung-Woo Choi
Submitted On:
6 July 2018 - 6:18am
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SAM2018_ByeonghoJo_20180709_ver2_forpdf.pdf

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[1] Byeongho Jo, Jung-Woo Choi, "Sine-based EB-ESPRIT for source localization", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3367. Accessed: Aug. 21, 2018.
@article{3367-18,
url = {http://sigport.org/3367},
author = {Byeongho Jo; Jung-Woo Choi },
publisher = {IEEE SigPort},
title = {Sine-based EB-ESPRIT for source localization},
year = {2018} }
TY - EJOUR
T1 - Sine-based EB-ESPRIT for source localization
AU - Byeongho Jo; Jung-Woo Choi
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3367
ER -
Byeongho Jo, Jung-Woo Choi. (2018). Sine-based EB-ESPRIT for source localization. IEEE SigPort. http://sigport.org/3367
Byeongho Jo, Jung-Woo Choi, 2018. Sine-based EB-ESPRIT for source localization. Available at: http://sigport.org/3367.
Byeongho Jo, Jung-Woo Choi. (2018). "Sine-based EB-ESPRIT for source localization." Web.
1. Byeongho Jo, Jung-Woo Choi. Sine-based EB-ESPRIT for source localization [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3367

A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar


Sea clutters with Doppler-varying spectrum exert a
notable negative impact on the detection performance, especially
with low-velocity targets, when a passive bistatic radar is employed
to detect sea-surface targets. One feasible solution is to
modulate the reference signal onto the Doppler dimension and, as
such, a filter with a wide notch and sharp edges can be obtained
to suppress the residual clutters. However, to achieve this goal, a
considerably high computational complexity is demanded in the

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Authors:
Yahui Ma, Shengheng Liu,Jun Lu
Submitted On:
5 July 2018 - 11:53pm
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[非密]A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar.pptx

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[1] Yahui Ma, Shengheng Liu,Jun Lu, "A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3364. Accessed: Aug. 21, 2018.
@article{3364-18,
url = {http://sigport.org/3364},
author = {Yahui Ma; Shengheng Liu;Jun Lu },
publisher = {IEEE SigPort},
title = {A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar},
year = {2018} }
TY - EJOUR
T1 - A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar
AU - Yahui Ma; Shengheng Liu;Jun Lu
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3364
ER -
Yahui Ma, Shengheng Liu,Jun Lu. (2018). A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar. IEEE SigPort. http://sigport.org/3364
Yahui Ma, Shengheng Liu,Jun Lu, 2018. A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar. Available at: http://sigport.org/3364.
Yahui Ma, Shengheng Liu,Jun Lu. (2018). "A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar." Web.
1. Yahui Ma, Shengheng Liu,Jun Lu. A Multi-Channel Partial-Update Algorithm for Sea Clutter Suppression in Passive Bistatic Radar [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3364

Performance analysis of distributed radio interferometric calibration


Distributed calibration based on consensus optimization is a computationally efficient method to calibrate large radio interferometers such as LOFAR and SKA. Calibrating along multiple directions in the sky and removing the bright foreground signal is a crucial step in many science cases in radio interferometry. The residual data contain weak signals of huge scientific interest and of particular concern is the effect of incomplete sky models used in calibration on the residual. In order to study this, we consider the mapping between the input uncalibrated data and the output residual data.

lofar75.pdf

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17 July 2018 - 6:22am
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lofar75.pdf

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lofar75.pdf

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[1] , "Performance analysis of distributed radio interferometric calibration", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3358. Accessed: Aug. 21, 2018.
@article{3358-18,
url = {http://sigport.org/3358},
author = { },
publisher = {IEEE SigPort},
title = {Performance analysis of distributed radio interferometric calibration},
year = {2018} }
TY - EJOUR
T1 - Performance analysis of distributed radio interferometric calibration
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3358
ER -
. (2018). Performance analysis of distributed radio interferometric calibration. IEEE SigPort. http://sigport.org/3358
, 2018. Performance analysis of distributed radio interferometric calibration. Available at: http://sigport.org/3358.
. (2018). "Performance analysis of distributed radio interferometric calibration." Web.
1. . Performance analysis of distributed radio interferometric calibration [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3358

Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations


RF 30 GHz ray-tracing simulation results are presented from a conceptual, Massive- Multiple Input Multiple Output (M-MIMO) propagation model in an urban canyon. The usage of Constant Envelope (CE) RF signals is evaluated in both

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Authors:
Edward A Ball
Submitted On:
28 June 2018 - 8:13am
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SAMS_post00000001.pdf

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[1] Edward A Ball, "Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3335. Accessed: Aug. 21, 2018.
@article{3335-18,
url = {http://sigport.org/3335},
author = {Edward A Ball },
publisher = {IEEE SigPort},
title = {Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations},
year = {2018} }
TY - EJOUR
T1 - Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations
AU - Edward A Ball
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3335
ER -
Edward A Ball. (2018). Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations. IEEE SigPort. http://sigport.org/3335
Edward A Ball, 2018. Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations. Available at: http://sigport.org/3335.
Edward A Ball. (2018). "Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations." Web.
1. Edward A Ball. Constant Envelope Transceivers in Millimetre-Wave Massive MIMO: EVM and Link Budget Considerations [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3335

A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT

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19 April 2018 - 9:35pm
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ICASSP2018_poster.pdf

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[1] , "A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3050. Accessed: Aug. 21, 2018.
@article{3050-18,
url = {http://sigport.org/3050},
author = { },
publisher = {IEEE SigPort},
title = {A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT},
year = {2018} }
TY - EJOUR
T1 - A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3050
ER -
. (2018). A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT. IEEE SigPort. http://sigport.org/3050
, 2018. A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT. Available at: http://sigport.org/3050.
. (2018). "A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT." Web.
1. . A DEEP NEURAL NETWORK BASED METHOD OF SOURCE LOCALIZATION IN A SHALLOWWATER ENVIRONMENT [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3050

Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar


The millimeter wave WLAN standard can be used for joint communication-radar by exploiting the waveform preamble as a radar pulse. The velocity estimation accuracy with this approach, however, is limited due to the short integration time. A physical increase in the radar pulse integration duration, however, leads to a decrease in the communication data rate.

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Authors:
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.
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21 April 2018 - 8:31pm
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Poster_VIRTUAL PULSE DESIGN FOR IEEE 802.11AD-BASED JOINT COMMUNICATION-RADAR.pdf

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[1] Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr., "Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2965. Accessed: Aug. 21, 2018.
@article{2965-18,
url = {http://sigport.org/2965},
author = {Preeti Kumari; Sergiy A. Vorobyov; and Robert W. Heath; Jr. },
publisher = {IEEE SigPort},
title = {Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar},
year = {2018} }
TY - EJOUR
T1 - Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar
AU - Preeti Kumari; Sergiy A. Vorobyov; and Robert W. Heath; Jr.
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2965
ER -
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.. (2018). Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar. IEEE SigPort. http://sigport.org/2965
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr., 2018. Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar. Available at: http://sigport.org/2965.
Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.. (2018). "Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar." Web.
1. Preeti Kumari, Sergiy A. Vorobyov, and Robert W. Heath, Jr.. Virtual Pulse Design for IEEE 802.11ad-Based Joint Communication-Radar [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2965

JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK

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18 April 2018 - 8:05am
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FrankLIN_Presentation_Joint tracking and separation v3_pptx.pdf

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FrankLIN_Presentation_Joint tracking and separation v3_pptx.pdf

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[1] , "JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2806. Accessed: Aug. 21, 2018.
@article{2806-18,
url = {http://sigport.org/2806},
author = { },
publisher = {IEEE SigPort},
title = {JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK},
year = {2018} }
TY - EJOUR
T1 - JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2806
ER -
. (2018). JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK. IEEE SigPort. http://sigport.org/2806
, 2018. JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK. Available at: http://sigport.org/2806.
. (2018). "JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK." Web.
1. . JOINTLY TRACKING AND SEPARATING SPEECH SOURCES USING MULTIPLE FEATURES AND THE GENERALIZED LABELED MULTI-BERNOULLI FRAMEWORK [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2806

Joint Estimation of the Room Geometry and Modes with Compressed Sensing


Acoustical behavior of a room for a given position of microphone and sound source is usually described using the room impulse response. If we rely on the standard uniform sampling, the estimation of room impulse response for arbitrary positions in the room requires a large number of measurements. In order to lower the required sampling rate, some solutions have emerged that exploit the sparse representation of the room wavefield in the terms of plane waves in the low-frequency domain. The plane wave representation has a simple form in rectangular rooms.

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13 April 2018 - 10:07am
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Joint Estimation of the Room Geometry and Modes with Compressed Sensing.pdf

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[1] , "Joint Estimation of the Room Geometry and Modes with Compressed Sensing", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2708. Accessed: Aug. 21, 2018.
@article{2708-18,
url = {http://sigport.org/2708},
author = { },
publisher = {IEEE SigPort},
title = {Joint Estimation of the Room Geometry and Modes with Compressed Sensing},
year = {2018} }
TY - EJOUR
T1 - Joint Estimation of the Room Geometry and Modes with Compressed Sensing
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2708
ER -
. (2018). Joint Estimation of the Room Geometry and Modes with Compressed Sensing. IEEE SigPort. http://sigport.org/2708
, 2018. Joint Estimation of the Room Geometry and Modes with Compressed Sensing. Available at: http://sigport.org/2708.
. (2018). "Joint Estimation of the Room Geometry and Modes with Compressed Sensing." Web.
1. . Joint Estimation of the Room Geometry and Modes with Compressed Sensing [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2708

OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT


In this work, we consider the problem of synchronising separately located transmitters and a staring array receiver that also has a local transmitter. The acknowledged benefits of using separate transmitters in active sensing are often undermined by the difficulty in accurate synchronisation of the receiver and the transmitters. In this work, we propose a solution that is based on measurements from non-cooperative objects in the illuminated region. We formulate the problem as parameter estimation in a state space model with individual transmitter channel data cubes as measurements.

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Authors:
Kimin Kim, Murat Uney, Bernard Mulgrew
Submitted On:
15 April 2018 - 12:07am
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ICASSP_2018_Kimin_Kim_Poster

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[1] Kimin Kim, Murat Uney, Bernard Mulgrew, "OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2463. Accessed: Aug. 21, 2018.
@article{2463-18,
url = {http://sigport.org/2463},
author = {Kimin Kim; Murat Uney; Bernard Mulgrew },
publisher = {IEEE SigPort},
title = {OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT},
year = {2018} }
TY - EJOUR
T1 - OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT
AU - Kimin Kim; Murat Uney; Bernard Mulgrew
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2463
ER -
Kimin Kim, Murat Uney, Bernard Mulgrew. (2018). OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT. IEEE SigPort. http://sigport.org/2463
Kimin Kim, Murat Uney, Bernard Mulgrew, 2018. OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT. Available at: http://sigport.org/2463.
Kimin Kim, Murat Uney, Bernard Mulgrew. (2018). "OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT." Web.
1. Kimin Kim, Murat Uney, Bernard Mulgrew. OPPORTUNISTIC SYNCHRONISATION OF MULTI-STATIC STARING ARRAY RADARS VIA TRACK-BEFORE-DETECT [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2463

MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING


Seismic traces recorded in a single sensor from multiple shots demonstrate significant correlation. We propose a memory-assisted seismic signal compression method based on dictionary learning and sparse coding that would explore this correlation. Different from traditional methods, the dictionary used for compression is learned and updated by the information extracted from the common memory between the sender (sensor) node and the receiver node, over a fixed window of the most recent traces. The common memory is formed by the previously transmitted traces.

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Authors:
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri
Submitted On:
10 November 2017 - 9:34am
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MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING

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[1] Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri, "MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2292. Accessed: Aug. 21, 2018.
@article{2292-17,
url = {http://sigport.org/2292},
author = {Xin Tian; Afshin Abdi; Entao Liu; Faramarz Fekri },
publisher = {IEEE SigPort},
title = {MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING},
year = {2017} }
TY - EJOUR
T1 - MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING
AU - Xin Tian; Afshin Abdi; Entao Liu; Faramarz Fekri
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2292
ER -
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri. (2017). MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING. IEEE SigPort. http://sigport.org/2292
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri, 2017. MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING. Available at: http://sigport.org/2292.
Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri. (2017). "MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING." Web.
1. Xin Tian, Afshin Abdi, Entao Liu, Faramarz Fekri. MEMORY-ASSISTED SEISMIC SIGNAL COMPRESSION BASED ON DICTIONARY LEARNING AND SPARSE CODING [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2292

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