Results 231 to 240 of about 102,342 (297)

Robust recursive estimation for the errors-in-variables nonlinear systems with impulsive noise. [PDF]

Sci Rep
Wang X, Zhu F.
europepmc   +1 more source

High impedance faults detection in power distribution networks using rogowski coils, kalman filtering, least-squares and non-recursive DFT computation engines. [PDF]

PLoS One
Ali ZM, Mostafa MH, Abdel Aleem SHE, Esmail EM.   +3 more
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Application of untargeted plasma metabolomics and machine learning to construct a diagnostic model for hypertrophic cardiomyopathy: a case-control study. [PDF]

Metabolomics
Li R, Wang B, Shan B, Sun M, Ta S, Zhao J, Kang N, Yang F, Yuan Y, Li X, Wang H, Fan L, Zheng H, Wang J, Liu L.   +14 more
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A drift-aware RS²FS pipeline with confidence gating for IDS. [PDF]

Sci Rep
Sakthivel G, Kumarasamy AK.
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Radiomics based on habitat analysis in predicting parametrial invasion of early stage cervical cancer. [PDF]

Front Oncol
Yang C, Li M, Yang C, Jiang P, Yang C, Dai J, Chen B, Wang W, Qin Z, Shi T, Yi X, Jin Z.   +11 more
europepmc   +1 more source

Self-learning type-2 fuzzy systems with adaptive rule reduction for time series forecasting. [PDF]

PeerJ Comput Sci
Alkharashi A, Kaur G, Alsolai H, Dafaalla H, Asklany S, Alrusaini O, Alqazzaz A, Alshammeri M.   +7 more
europepmc   +1 more source

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Statistically linearized recursive least squares

2010 IEEE International Workshop on Machine Learning for Signal Processing, 2010
This article proposes a new interpretation of the sigmapoint kalman filter (SPKF) for parameter estimation as being a statistically linearized recursive least-squares algorithm. This gives new insight on the SPKF for parameter estimation and particularly this provides an alternative proof for a result of Van der Merwe. On the other hand, it legitimates
Geist, Matthieu, Pietquin, Olivier
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Recursive moving least squares

Engineering Analysis with Boundary Elements, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hamid Mehrabi, Behzad Voosoghi
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Microstatistic recursive least squares

Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94, 2002
A piecewise-linear signal model based on amplitude threshold decomposition underlies the idea of microstatistic nonlinear signal characterization. This model is easily incorporated into many existing linear signal processing techniques and leads to algorithms that are robust (e.g., tolerant of non-Gaussian noise) and that are applicable to nonlinear ...
S. Knudsen, D. Keddy
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