Comparison of the convergence rates of the new correntropy-based Levenberg-Marquardt (CLM) method and the fixed-point maximum correntropy (FP-MCC) algorithm
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Publication:2312514
DOI10.1007/s00034-017-0694-3zbMath1411.94031OpenAlexW2766617485MaRDI QIDQ2312514
Ahmad Reza Heravi, Ghosheh Abed Hodtani
Publication date: 17 July 2019
Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00034-017-0694-3
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Cites Work
- Unnamed Item
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- A novel convergence accelerator for the LMS adaptive filter
- A mutual information extension to the matched filter
- Rate of convergence of the generalized Newton algorithm using the fixed- point approach
- On the quadratic convergence of the Levenberg-Marquardt method without nonsingularity assumption
- A recursive parameter estimator yielding exponential convergence under sufficient excitation
- Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty
- An adaptive Gauss-Newton algorithm for training multilayer nonlinear filters that have embedded memory
- Two improved normalized subband adaptive filter algorithms with good robustness against impulsive interferences
- A time delay estimation algorithm based on the weighted correntropy spectral density
- Steady-state tracking analysis of adaptive filter with maximum correntropy criterion
- Observer-Based Fault Detection for Nonlinear Systems With Sensor Fault and Limited Communication Capacity
- The modified Levenberg-Marquardt method for nonlinear equations with cubic convergence
- An Algorithm for Least-Squares Estimation of Nonlinear Parameters
- Exponential convergence of the Kalman filter based parameter estimation algorithm
- Observer-based approach to fault detection and isolation for nonlinear systems
- Correntropy: Properties and Applications in Non-Gaussian Signal Processing
- Adaptive multitask network based on maximum correntropy learning algorithm
- Information Theoretic Learning
- Robust Principal Component Analysis Based on Maximum Correntropy Criterion
- On Estimation of a Probability Density Function and Mode
- A method for the solution of certain non-linear problems in least squares
- Learning from examples with information theoretic criteria
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