Suchergebnisse - "sparse RLS algorithm"

Online sequential echo state network with sparse RLS algorithm for time series prediction

Autoren: Lei Wang Kaizhe Nie Zohaib Ahmad et al.

Quelle: Neural Networks. 118:32-42

Schlagwörter: Time Factors, 0202 electrical engineering, electronic engineering, information engineering, Neural Networks, Computer, 02 engineering and technology, Least-Squares Analysis, Algorithms, Forecasting

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/31228722
https://dblp.uni-trier.de/db/journals/nn/nn118.html#YangQANW19
https://doi.org/10.1016/j.neunet.2019.05.006
https://www.ncbi.nlm.nih.gov/pubmed/31228722
https://www.wikidata.org/entity/Q92954944
https://www.sciencedirect.com/science/article/pii/S0893608019301388

A new diffusion sparse RLS algorithm with improved convergence characteristics

Autoren: Bijit Kumar Das Mrityunjoy Chakraborty

Quelle: 2016 IEEE International Symposium on Circuits and Systems (ISCAS). :2651-2654

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ieeexplore.ieee.org/document/7539138
https://dblp.uni-trier.de/db/conf/iscas/iscas2016.html#DasC16

Correntropy Induced Metric Penalized Sparse RLS Algorithm to Improve Adaptive System Identification

Autoren: Linglong Dai Baoyu Zheng Li Xu et al.

Quelle: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring). :1-5

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Zugangs-URL: https://dblp.uni-trier.de/db/conf/vtc/vtc2016s.html#GuiDZXA16
http://ieeexplore.ieee.org/document/7504179/
https://ieeexplore.ieee.org/document/7504179/
https://tohoku.pure.elsevier.com/en/publications/correntropy-induced-metric-penalized-sparse-rls-algorithm-to-impr

Order-Extended Sparse RLS Algorithm for Doubly-Selective MIMO Channel Estimation

Autoren: R. Annavajjala Philip Orlik Toshiaki Koike-Akino et al.

Quelle: 2011 IEEE International Conference on Communications (ICC). :1-6

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences

Zugangs-URL: https://dblp.uni-trier.de/db/conf/icc/icc2011.html#Koike-AkinoMPAO11
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005963228
https://ieeexplore.ieee.org/document/5963228/
http://dblp.uni-trier.de/db/conf/icc/icc2011.html#Koike-AkinoMPAO11

A Modified Recursive Regularization Factor Calculation for Sparse RLS Algorithm with l1-Norm

Autoren: Junseok Lim Keunhwa Lee Seokjin Lee

Quelle: Mathematics, Vol 9, Iss 13, p 1580 (2021)

Schlagwörter: sparse impulse response system, sparse system estimation, l1-RLS, regularization factor, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2227-7390/9/13/1580; https://doaj.org/toc/2227-7390

Zugangs-URL: https://doaj.org/article/d80f4a16eb454367896376841a70d510

SPARLS: The Sparse RLS Algorithm

Autoren: Babadi, Behtash Kalouptsidis, Nicholas Tarokh, Vahid

Quelle: IEEE Transactions on Signal Processing. 58:4013-4025

Schlagwörter: adaptive filters, sparse system identification, compressed sensing

Dateibeschreibung: application/pdf

Zugangs-URL: https://dash.harvard.edu/bitstream/handle/1/4687196/tsp_sparls_2010.pdf?sequence%3D1
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005446434
https://dash.harvard.edu/handle/1/4687196
https://ieeexplore.ieee.org/document/5446434/
https://dblp.uni-trier.de/db/journals/tsp/tsp58.html#BabadiKT10
https://www.infona.pl/resource/bwmeta1.element.ieee-art-000005446434
http://dsp.rice.edu/sites/dsp.rice.edu/files/cs/sparls-tsp10.pdf
http://ui.adsabs.harvard.edu/abs/2010ITSP...58.4013B/abstract
https://pergamos.lib.uoa.gr/uoa/dl/object/3036857

Recursive regularisation parameter selection for sparse RLS algorithm

Autoren: Youwen Zhang Lu Liu Dajun Sun

Quelle: Electronics Letters. 54:286-287

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ui.adsabs.harvard.edu/abs/2018ElL....54..286S/abstract
https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/el.2017.4242
https://digital-library.theiet.org/content/journals/10.1049/el.2017.4242
https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/el.2017.4242

SPARLS: The sparse RLS algorithm

Autoren: Babadi, B. Kalouptsidis, N. Tarokh, V.

Zugangs-URL: https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3036857

1SPARLS: The Sparse RLS Algorithm

Autoren: Citable Link Behtash Babadi Nicholas Kalouptsidis et al.

Weitere Verfasser: Citable Link Behtash Babadi Nicholas Kalouptsidis et al.

Quelle: http://dash.harvard.edu/bitstream/handle/1/4687196/tsp_sparls_2010.pdf?sequence=1.

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.476.3313; http://dash.harvard.edu/bitstream/handle/1/4687196/tsp_sparls_2010.pdf?sequence=1

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.476.3313
http://dash.harvard.edu/bitstream/handle/1/4687196/tsp_sparls_2010.pdf?sequence=1

SPARLS: The Sparse RLS Algorithm

Autoren: Behtash Babadi Nicholas Kalouptsidis Vahid Tarokh et al.

Weitere Verfasser: Behtash Babadi Nicholas Kalouptsidis Vahid Tarokh et al.

Quelle: http://dsp.rice.edu/files/cs/sparls-tsp10.pdf.

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.168.6295

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.168.6295
http://dsp.rice.edu/files/cs/sparls-tsp10.pdf

SPARLS: The sparse RLS algorithm

Autoren: Babadi, B. Kalouptsidis, N. Tarokh, V.

Relation: uoadl:3036857; https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3036857

Verfügbarkeit: https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3036857

Correntropy Induced Metric Penalized Sparse RLS Algorithm to Improve Adaptive System Identification.

Autoren: Gui, Guan Dai, Linglong Zheng, Baoyu et al.

Quelle: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring); 2016, p1-5, 5p

Recursive regularisation parameter selection for sparse RLS algorithm.

Autoren: Dajun Sun Lu Liu Youwen Zhang

Quelle: Electronics Letters (Wiley-Blackwell); 3/8/2018, Vol. 54 Issue 5, p286-287, 2p

Schlagwörter: LEAST squares, CONVEX functions, MEAN square algorithms, REAL variables, ALGORITHMS

Recursive regularisation parameter selection for sparse RLS algorithm.

Autoren: Sun, Dajun Liu, Lu Zhang, Youwen

Quelle: Electronics Letters (Wiley-Blackwell); Mar2018, Vol. 54 Issue 6, p286-287, 2p

Order-Extended Sparse RLS Algorithm for Doubly-Selective MIMO Channel Estimation.

Autoren: Koike-Akino, T. Molisch, A.F. Man-On Pun et al.

Quelle: 2011 IEEE International Conference on Communications (ICC); 2011, p1-6, 6p

A Modified Recursive Regularization Factor Calculation for Sparse RLS Algorithm with l 1 -Norm.

Autoren: Lim, Junseok Lee, Keunhwa Lee, Seokjin

Quelle: Mathematics (2227-7390); Jul2021, Vol. 9 Issue 13, p1580-1580, 1p

Schlagwörter: IMPULSE response, COMPUTATIONAL complexity, MATHEMATICAL regularization, ALGORITHMS, PRIOR learning

Channel sparsity aware polynomial expansion filters for nonlinear acoustic echo cancellation

Autoren: Vinith Vijayarajan

Schlagwörter: Electrical engineering not elsewhere classified, Acoustics and noise control (excl. architectural acoustics), Nonlinear acoustic echo cancellation, system identification, 3rd order volterra filter, functional link adaptive filter, even mirror fourier nonlinear filter, sparse RLS algorithm, sparse LMS algorithm, Electrical and Electronic Engineering not elsewhere classified

Relation: https://figshare.com/articles/thesis/Channel_sparsity_aware_polynomial_expansion_filters_for_nonlinear_acoustic_echo_cancellation/7464584

Verfügbarkeit: https://doi.org/10.25394/pgs.7464584.v1

Reservoir computing for predicting pm 2.5 dynamics in a metropolis.

Autoren: Sergeev, Aleksandr Shichkin, Andrey Buevich, Alexander et al.

Quelle: European Physical Journal: Special Topics; Oct2025, Vol. 234 Issue 15, p4597-4605, 9p

Schlagwörter: PARTICULATE matter, FORECASTING, RECURRENT neural networks, ENVIRONMENTAL sciences, DYNAMIC models, ARTIFICIAL neural networks, METROPOLITAN areas, PREDICTIVE validity

Geografische Kategorien: SEOUL (Korea), SOUTH Korea

Adaptive Channel Equalization Method Based on VARS-RLS in Underwater Acoustic Environment.

Autoren: Wu, Yujie Cui, Hengrong

Quelle: Journal of Physics: Conference Series; 2025, Vol. 3106 Issue 1, p1-9, 9p

Channel sparsity aware polynomial expansion filters for nonlinear acoustic echo cancellation

Autoren: Vinith Vijayarajan (5930993)

Schlagwörter: Electrical and Electronic Engineering not elsewhere classified, Acoustics and Noise Control (excl. Architectural Acoustics), Nonlinear acoustic echo cancellation, system identification, 3rd order volterra filter, functional link adaptive filter, even mirror fourier nonlinear filter, sparse RLS algorithm, sparse LMS algorithm

Relation: https://figshare.com/articles/Channel_sparsity_aware_polynomial_expansion_filters_for_nonlinear_acoustic_echo_cancellation/7464584