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of 10
pro vyhledávání: '"Islam Hassani"'
Publikováno v:
Analog Integrated Circuits and Signal Processing. 114:51-73
Publikováno v:
Traitement du Signal. 39:11-19
Robust algorithms applied in Acoustic Echo Cancellation systems present an excessive calculation load that has to be minimized. In the present paper, we propose two different low complexity fast least squares algorithms, called Partial Update Simplif
Autor:
Islam Hassani
Publikováno v:
Algerian Journal of Renewable Energy and Sustainable Development. 3:175-189
In this paper, we present the most used adaptive filtering algorithms such as Least Mean Square (LMS) and its normalized version NLMS with their advantages and drawbacks, and then show how the Variable Step Size (VSS) algorithms have been proposed to
Publikováno v:
2022 2nd International Conference on Advanced Electrical Engineering (ICAEE).
Publikováno v:
2022 2nd International Conference on Advanced Electrical Engineering (ICAEE).
Publikováno v:
Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities ISBN: 9783030920371
Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities
Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f76530baa5e59657374914a38933015
https://doi.org/10.1007/978-3-030-92038-8_51
https://doi.org/10.1007/978-3-030-92038-8_51
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811564024
In this paper, we introduce a Fast Normalized Least Mean square algorithm (FNLMS) to eliminate the acoustic echo in the presence of double talk signal. When the near-end speech is present the performance of the adaptive filtering is degraded, thus, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::404161e796d8bc73369463980a72a576
https://doi.org/10.1007/978-981-15-6403-1_90
https://doi.org/10.1007/978-981-15-6403-1_90
Publikováno v:
Applied Acoustics. 163:107210
In order to improve the performances of the Fast Normalized Least Mean Square type (FNLMS) adaptive filtering algorithm in the context of Acoustic Echo Cancellation (AEC), this work proposes an Improved Set Membership version by exploiting, firstly,
Publikováno v:
2018 International Conference on Communications and Electrical Engineering (ICCEE).
In this communication, fast adaptive algorithms are suggested to enhance the performance of the Fast- Normalized Least Mean Square (FNLMS) algorithm in Acoustic Echo Cancellation (AEC) applications with a sparse system. We propose two new algorithms,
Publikováno v:
2018 International Conference on Signal, Image, Vision and their Applications (SIVA).
This communication deals with the problem of Acoustic Echo Cancellation (AEC) by reduced complexity adaptive filtering algorithms. In this context, we propose to use the Set-Membership filtering concept with the Fast Normalized Least Mean Square Algo