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Alexander Jourjine

dblp:36/234 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › signal processing for communications
array signal processing
0.011999
Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics · NIPS 1999
Physical-layer communications › signal processing for communications › array signal processing
direction-of-arrival estimation
0.011999
Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics · NIPS 1999
Physical-layer communications › signal processing for communications › statistical signal processing › estimation theory
second-order statistics estimation
0.011999
Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics · NIPS 1999

Methods — techniques the papers use, named apart from their topics

second-order statistics · 0.0
YearPublicationVenuePosition
2000 Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixtures
abstract
We present a novel method for blind separation of any number of sources using only two mixtures. The method applies when sources are (W-)disjoint orthogonal, that is, when the supports of the (windowed) Fourier transform of any two signals in the mixture are disjoint sets. We show that, for anechoic mixtures of attenuated and delayed sources, the method allows one to estimate the mixing parameters by clustering ratios of the time-frequency representations of the mixtures. The estimates of the mixing parameters are then used to partition the time-frequency representation of one mixture to recover the original sources. The technique is valid even in the case when the number of sources is larger than the number of mixtures. The general results are verified on both speech and wireless signals.
Alexander Jourjine, Scott T. Rickard, Özgür Yilmaz
ICASSP1
1999 Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics
Justinian P. Rosca, Joseph Ó Ruanaidh, Alexander Jourjine, Scott T. Rickard
NIPS3