Results 211 to 220 of about 16,616 (239)

Adaptive Filtering Under a Variable Kernel Width Maximum Correntropy Criterion

IEEE Transactions on Circuits and Systems II: Express Briefs, 2017
The maximum correntropy criterion (MCC) algorithm with constant kernel width leads to a tradeoff problem in terms of convergence rate and steady-state misalignment. Thus, this brief proposes a variable kernel width (VKW) MCC algorithm to overcome this problem. The optimal kernel width of the proposed VKW-MCC algorithm is calculated at each iteration by
Sheng Zhang, Fuyi Huang, Jiashu Zhang
exaly   +3 more sources

An adaptive kernel width update method of correntropy for channel estimation

2015 IEEE International Conference on Digital Signal Processing (DSP), 2015
The maximum correntropy criterion (MCC) is a robust adaptation criterion, which has been successfully applied in various signal processing applications. The kernel width plays an important role in MCC adaptive filtering and has significant influence on convergence rate and steady-state performance.
JOSÉ Principe, Badong Chen
exaly   +2 more sources

AKSNet: A novel convolutional neural network with adaptive kernel width and sparse regularization for machinery fault diagnosis

Journal of Manufacturing Systems, 2021
Abstract Convolutional kernels have significant affections on feature learning of convolutional neural network (CNN). However, it is still a challenging problem to determine appropriate kernel width. Moreover, some features learned by convolutional layers are still redundant and noisy. Thus, adaptive selection of kernel width and feature selection of
Zhuang Ye, Jianbo Yu
exaly   +2 more sources

Dictionary Learning for Gaussian Kernel Adaptive Filtering with Variablekernel Center and Width

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
This paper establishes an adaptive update method for the Gaussian kernel parameters in the application to the kernel adaptive filtering (KAF). In this method, the kernel parameters are all adaptive and data-driven, although they should be given or estimated by cross-validation.
Toshihisa Tanaka, Kosuke Fukumori, Tomoya Wada   +2 more
exaly   +2 more sources

Remaining Useful Life Prediction of Kernel Density Estimation Based on Adaptive Window Width

Mechanisms and Machine Science, 2021
The kernel density estimation method is completely based on the data instead of the assumption distribution models considering the data-driven remaining useful life prediction. Among them, window width is an important parameter, and the selection of window width directly affects the accuracy of the final prediction results.
Xiuquan Sun, Fengshou Gu, Gu Fengshou
exaly   +2 more sources

Adaptive Kernel Width fourth order Maximum Correntropy based VSC control of grid-tied PV-Battery System

2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, 2021
The presented paper reports the adaptive kernel width fourth-order maximum correntropy criteria (AKWFOMCC) based voltage source converter (VSC) control for 3-phase 3-wire grid-tied dual-stage PV-battery system. The presented control executes numerous objectives, i.e., load balancing, power balancing, reactive power compensation, and maintains the unity
Ikhlaq Hussain, Aijaz Ahmad, Mukul Chankaya   +2 more
exaly   +2 more sources

A robust diffusion recursive generalized modified Blake-Zisserman algorithm for distributed estimation under an adaptive kernel width

Signal Processing, 2023
Alireza Naeimi Sadigh
exaly   +2 more sources

The normalized subband adaptive filter under variable kernel width maximum correntropy criterion for sparse system

2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE), 2023
Qianqian Liu, Zhigang Li, Yigang He
exaly   +2 more sources

Variable Kernel Width Algorithm in Constrained Maximum Complex Correntropy Criterion for Adaptive Beamforming

Circuits, Systems, and Signal Processing
Kanika Agarwal
exaly   +2 more sources

Kernel width adaptation in information theoretic cost functions

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010
This paper presents an algorithm for online adaptation of the kernel width parameter in information theoretic cost functions used for adaptive system training. Training algorithms which optimize information theoretic quantities like entropy involve choosing a kernel size for their sample estimators.
Abhishek Singh, José C. Príncipe
openaire   +1 more source