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pro vyhledávání: '"Mahmoud K. Madi"'
Autor:
Mahmoud K Madi, Fadi N Karameh
Publikováno v:
PLoS ONE, Vol 12, Iss 7, p e0181513 (2017)
Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended
Externí odkaz:
https://doaj.org/article/5b259c4536824bb2b10ef6aa2064ebc7
Autor:
Fadi N. Karameh, Mahmoud K. Madi
Publikováno v:
Journal of neural engineering. 15(4)
OBJECTIVE Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using expe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e96f6138540b4db0a9e7063d46bc0ee
https://pubmed.ncbi.nlm.nih.gov/29749350
https://pubmed.ncbi.nlm.nih.gov/29749350
Autor:
Fadi N. Karameh, Mahmoud K. Madi
Publikováno v:
2016 3rd Middle East Conference on Biomedical Engineering (MECBME).
The Kalman Filter (KF) is a powerful state estimation technique developed for linear time-varying systems and has recently extended for estimating nonlinear time varying dynamical systems. However, a major challenge for this technique is the choice o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08e6506b91c9edd8c8066068d604aee5
https://doi.org/10.1109/mecbme.2016.7745400
https://doi.org/10.1109/mecbme.2016.7745400
Autor:
Mahmoud K. Madi, Fadi N. Karameh
Publikováno v:
2015 International Conference on Advances in Biomedical Engineering (ICABME).
Recent advent of the nonlinear Cubature Kalman Filter (CKF) allows for stable parametric estimation in inherently nonlinear systems driven by random inputs of Gaussian nature. As with any estimation technique, the solution accuracy remains dependent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::548662238ce06724b4d10e7a7f8a7608
https://doi.org/10.1109/icabme.2015.7323267
https://doi.org/10.1109/icabme.2015.7323267
Autor:
Fadi N. Karameh, Mahmoud K. Madi
Publikováno v:
PLoS ONE
PLoS ONE, Vol 12, Iss 7, p e0181513 (2017)
PLoS ONE, Vol 12, Iss 7, p e0181513 (2017)
Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a47e3e400f79589c3a621ec00c51aaf
https://doi.org/10.1371/journal.pone.0181513
https://doi.org/10.1371/journal.pone.0181513
Autor:
Fadi N. Karameh, Mahmoud K. Madi
Publikováno v:
2011 1st Middle East Conference on Biomedical Engineering.
Sensory systems in mammals and humans are tuned to localize object in the environment in an accurate and behaviorally independent manner. While many engineering approaches can be used, it is less clear how nature solves the problem of object localiza
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b5a343be739306bc62054f1c37c629c
https://doi.org/10.1109/mecbme.2011.5752054
https://doi.org/10.1109/mecbme.2011.5752054
Autor:
Mahmoud K Madi, Fadi N Karameh
Publikováno v:
Journal of Neural Engineering; Aug2018, Vol. 15 Issue 4, p1-1, 1p