Results 271 to 280 of about 195,151 (333)

Multichannel blind separation of speech signals in a reverberant environment

, 2001
Muhammad Z. Ikram
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Enhancing the Performance of Si/Ga₂O₃ Heterojunction Solar-Blind Photodetectors for Underwater Applications. [PDF]

Nanomaterials (Basel)
Li N, Liao Z, Peng L, Xue D, Peng K, Lv P.   +5 more
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Balancing Objectivity and Welfare: Physiological and Behavioural Responses of Guide Dogs During an Independent Certification Protocol. [PDF]

Animals (Basel)
Faerber-Morak V, Glenk LM, Weissenbacher K, Bremhorst A.   +3 more
europepmc   +1 more source

Tandem split-GFP influenza A viruses for sensitive and accurate replication analyses. [PDF]

Microbiol Spectr
Nath H, Arndt A, Mann JT, Baker SF.
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Effects of Spatial and Signal-Imposed Noises on Motor Unit Decomposition

Taleshi M, Yeung D, Negro F, Vujaklija I.   +3 more
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Blind Source Separation of Graph Signals

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
With a change of signal notion to graph signal, new means of performing blind source separation (BSS) appear. Particularly, existing independent component analysis (ICA) methods exploit the non-Gaussianity of the signals or other types of prior information.
Vorobyov, Sergiy A., Ollila, Esa, Miettinen, Jari   +3 more
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Blind signal separation revisited

Proceedings of the 36th IEEE Conference on Decision and Control, 2002
Complex control and decision systems are very often confronted with an extensive amount of information about their environment from various sensors such as video cameras, etc. Hence, extraction of non-redundant signals from the available sensor information has become an important task in many control and decision problems.
D. Obradovic, G. Deco
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Blind signal separation using QMF

2015 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2015
Blind signal separation method is the method that the source signals are obtained by separating only the mixed signals. Generally, separation precision is lower when blind signal separation method is used for the sound signals. It is the cause that the power of the sound signals is concentrated in the low-frequency band.
Kazuaki Matsushima, Tomomi Ogawa, Hiroki Matsumoto   +2 more
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Blind signal separation using ICA

2001 International Conferences on Info-Tech and Info-Net. Proceedings (Cat. No.01EX479), 2002
In this paper, a steepest descent algorithm for independent component analysis (ICA) is proposed. In contrast to most blind source separation algorithms, the method does not employ higher order statistics. A pre-whitening procedure is performed to de-correlate the sensor (mixed) signals before extracting the vector. The proposed method is verified with
null Weidong Zhou, null Lei Jia
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