Optimized Bayesian adaptive resonance theory mapping model using a rational quadratic kernel and Bayesian quadratic regularization
S Yang, H Li, X Gou, C Bian, Q Shao - Applied Intelligence, 2022 - Springer
Bayesian adaptive resonance theory (ART) and ARTMAP-based neural network classifier
(known as BAM) are widely used and achieve good classification performance when solving …
(known as BAM) are widely used and achieve good classification performance when solving …
Optimal kernel selection based on GPR for adaptive learning of mean throughput rates in LTE networks
Abstract Machine learning models and algorithms have been employed in various
applications, from prognostic scrutinizing, learning and revealing patterns in data …
applications, from prognostic scrutinizing, learning and revealing patterns in data …
Enhancing localization accuracy in wireless sensor networks using range-free methods and RSS measurements
V Kalyani - 2018 International Conference on Recent Trends in …, 2018 - ieeexplore.ieee.org
Localization is a significant feature in the area of wireless sensor networks (WSNs).
Localization is computed through relation between localized node and unlocalized no de for …
Localization is computed through relation between localized node and unlocalized no de for …
A Multiple Kernel Minimum Entropy Kalman Filter
K Chen, Y Cheng, Z Li, Y Zhang - 2023 China Automation …, 2023 - ieeexplore.ieee.org
In this paper, a multiple kernel minimum error entropy Kalman filter is proposed to estimate
the filter state under abnormal measurement pollution. Firstly, an augmented Kalman filter …
the filter state under abnormal measurement pollution. Firstly, an augmented Kalman filter …