Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Neil J. Bershad"'
Publikováno v:
IEEE Transactions on Signal and Information Processing over Networks. 8:960-972
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e95806680b27f03edbef2c879f5cab2b
https://doi.org/10.1109/tsipn.2022.3223807
https://doi.org/10.1109/tsipn.2022.3223807
Publikováno v:
International Journal of Adaptive Control and Signal Processing. 35:2466-2486
The diffusion least mean square (DLMS) and the diffusion normalized least mean square (DNLMS) algorithms are analyzed for a network having a fusion center. This structure reduces the dimensionality of the resulting stochastic models while preserving
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::206102543bce224eb375dedf0d528c23
https://doi.org/10.1002/acs.3334
https://doi.org/10.1002/acs.3334
Publikováno v:
IEEE Transactions on Signal Processing. 68:676-686
This paper studies the stochastic behavior of the recursive least squares (RLS) algorithm in a system identification framework for a cyclostationary colored input. The input cyclostationary signal is modeled by a colored random process with periodica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a77e246bd10777044077fb5dc749d4e
https://doi.org/10.1109/tsp.2020.2964225
https://doi.org/10.1109/tsp.2020.2964225
Publikováno v:
Signal Processing. 160:127-136
This paper studies the stochastic behavior of the LMS algorithm for a system identification framework when the input signal is a cyclostationary colored Gaussian process. The unknown system is modeled by the standard random walk model. Well-known res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f07f6ee7ed2ea81a7bc71c7b0e025c63
https://doi.org/10.1016/j.sigpro.2019.02.018
https://doi.org/10.1016/j.sigpro.2019.02.018
Publikováno v:
Digital Signal Processing. 88:149-159
This paper studies the stochastic behavior of the LMS algorithm in a system identification framework for a cyclostationary colored input without assuming a Gaussian distribution for the input. The input cyclostationary signal is modeled by a colored
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec05e52311c08296fbc329f814c6296e
https://doi.org/10.1016/j.dsp.2019.02.011
https://doi.org/10.1016/j.dsp.2019.02.011
Publikováno v:
Signal Processing. 152:197-205
The analysis of saturation-type nonlinearities on the input and the error in the weight update equation for LMS adaptation were obtained for a stationary white Gaussian data model in [28] for system identification. Here the input signal is modeled by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6eaa91d90f40b60d1bc513fcdca05d58
https://doi.org/10.1016/j.sigpro.2018.05.023
https://doi.org/10.1016/j.sigpro.2018.05.023
Publikováno v:
IEEE Transactions on Signal Processing. 66:4753-4765
This paper studies the stochastic behavior of the LMS and NLMS algorithms in a system identification framework for a cyclostationary white input without assuming a Gaussian distribution for the input. The input cyclostationary signal is modeled by a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::649c5e97bdff42d291af1fae6d03f2e7
https://doi.org/10.1109/tsp.2018.2860552
https://doi.org/10.1109/tsp.2018.2860552
Publikováno v:
Signal Processing. 142:27-35
The effects of saturation-type nonlinearities on the input and the error in the weight update equation for LMS adaptation are investigated for a stationary white Gaussian data model for system identification. Nonlinear recursions are derived for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2a82012f58d4d17afdcea0eb57b35ad
https://doi.org/10.1016/j.sigpro.2017.06.005
https://doi.org/10.1016/j.sigpro.2017.06.005
Publikováno v:
Signal Processing. 185:108081
This paper studies the stochastic behavior of a specific version of the Diffusion Least-Mean Square (DLMS) algorithm in a system identification framework for a cyclostationary white Gaussian input. The considered DLMS version has a fusion center. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf8088bc85ad066b402758d0a08b5c5d
https://doi.org/10.1016/j.sigpro.2021.108081
https://doi.org/10.1016/j.sigpro.2021.108081
Publikováno v:
Signal Processing. 133:219-226
The purpose of this note is to point out that the recently proposed fractional least mean squares (FLMS) algorithm, whose derivation is based on fractional derivative, is not suitable for adaptive signal processing. Our claims are verified via extens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09d5ba6af31845fb237ce123775da911
https://doi.org/10.1016/j.sigpro.2016.11.009
https://doi.org/10.1016/j.sigpro.2016.11.009