Results 111 to 120 of about 543 (157)

An Improved Cubature Kalman Filter for GNSS-Denied and System-Noise-Varying INS/GNSS Navigation. [PDF]

Micromachines (Basel)
Liu D, Chen X, Cui B.
europepmc   +1 more source

A TLS-Motivated Non-Iterative Robust Square-Root Cubature Kalman Filter for Bearings-Only Tracking. [PDF]

Sensors (Basel)
Li C, Wu H, Zeng G, Yang M, Zhao Y, Mehmood A.   +5 more
europepmc   +1 more source

An intelligent hybrid approach combining fuzzy C-means and the sperm whale algorithm for cyber attack detection in IoT networks. [PDF]

Sci Rep
Elsedimy EI, AboHashish SMM.
europepmc   +1 more source

Robust Trajectory Prediction for Mobile Robots via Minimum Error Entropy Criterion and Adaptive LSTM Networks. [PDF]

Entropy (Basel)
Xie D, Li Z, Zhang C, Wang C, Wei X.
europepmc   +1 more source

Cost-Reference Particle Filter-Based Method for Constructing Effective Brain Networks: Application in Optically Pumped Magnetometer Magnetoencephalography. [PDF]

Bioengineering (Basel)
Ma Y, Liang X, Wu H, Lu H, Li Y, Liu C, Gao Y, Xiang M, Yu D, Ning X.   +9 more
europepmc   +1 more source

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Kernel recursive maximum correntropy

Signal Processing, 2015
In this letter, a robust kernel adaptive algorithm, called the kernel recursive maximum correntropy (KRMC), is derived in kernel space and under the maximum correntropy criterion (MCC). The proposed algorithm is particularly useful for nonlinear and non-Gaussian signal processing, especially when data contain large outliers or disturbed by impulsive ...
Wentao Ma, Badong Chen
exaly   +2 more sources

A distributed maximum correntropy Kalman filter

Signal Processing, 2019
Abstract Most distributed Kalman filters are based on the cost function of the well-known minimum mean square estimation criterion, which performs well in the presence of Gaussian noise. When impulsive noise is involved, the performance of distributed Kalman filters may become worse.
Gang Wang, Rui Xue
exaly   +2 more sources

Maximum Correntropy Estimation Is a Smoothed MAP Estimation

IEEE Signal Processing Letters, 2012
As a new measure of similarity, the correntropy can be used as an objective function for many applications. In this letter, we study Bayesian estimation under maximum correntropy (MC) criterion. We show that the MC estimation is, in essence, a smoothed maximum a posteriori (MAP) estimation, including the MAP and the minimum mean square error (MMSE ...
JOSÉ Principe, Badong Chen
exaly   +2 more sources

Convex regularized recursive maximum correntropy algorithm

Signal Processing, 2016
In this brief, a robust and sparse recursive adaptive filtering algorithm, called convex regularized recursive maximum correntropy (CR-RMC), is derived by adding a general convex regularization penalty term to the maximum correntropy criterion (MCC). An approximate expression for automatically selecting the regularization parameter is also introduced ...
Badong Chen, Kaixin Li
exaly   +2 more sources