UWB anchor nodes self-calibration in NLOS conditions: a machine learning and adaptive PHY error correction approach
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DOI: 10.1007/s11276-021-02631-0
Abstract: Ultra-wideband (UWB) positioning performance is highly related to the accuracy of the coordinates of the fixed anchor nodes, which form the system infrastructure. The process of determining the position of the anchors is called calibration.… read more here.
Keywords: machine learning; learning adaptive; calibration; anchor nodes ... See more keywords
Switched learning adaptive neuro-control strategy
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DOI: 10.1016/j.neucom.2019.12.139
Abstract: Abstract The generalized learning algorithm can be efficiently used as control strategy, but it has some drawbacks such as: sensitivity to the training dataset, poor robustness against changes in the system, difficulty to generate the… read more here.
Keywords: control; adaptive neuro; learning adaptive; switched learning ... See more keywords
Learning Adaptive Neighborhood Graph on Grassmann Manifolds for Video/Image-Set Subspace Clustering
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DOI: 10.1109/tmm.2020.2975394
Abstract: The objective of self-expression based spectral clustering is to learn an affinity matrix which accurately reflects the similarity among data, and the Laplacian constraint is usually exploited to make the affinity matrix preserve the global… read more here.
Keywords: grassmann manifolds; graph grassmann; learning adaptive; neighborhood ... See more keywords
Strain FBG-Based Sensor for Detecting Fence Intruders Using Machine Learning and Adaptive Thresholding
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DOI: 10.3390/s23115015
Abstract: This paper demonstrates an intruder detection system using a strain-based optical fiber Bragg grating (FBG), machine learning (ML), and adaptive thresholding to classify the intruder as no intruder, intruder, or wind at low levels of… read more here.
Keywords: learning adaptive; machine learning; intruder; fence ... See more keywords