Search Results - Quantized kernel recursive minimum error entropy
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Quantized kernel recursive minimum error entropy algorithm
ISSN: 0952-1976, 1873-6769Published: Elsevier Ltd 01.05.2023Published in Engineering applications of artificial intelligence (01.05.2023)“…In this paper, we propose a online vector quantization (VQ) method based on the kernel recursive minimum error entropy (KRMEE) algorithm…”
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Generalized minimum error entropy for robust learning
ISSN: 0031-3203Published: 01.03.2023Published in Pattern recognition (01.03.2023)Get full text
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Diffusion Quantized Recursive Mixture Minimum Error Entropy Algorithm
ISSN: 1549-7747, 1558-3791Published: New York IEEE 01.12.2022Published in IEEE transactions on circuits and systems. II, Express briefs (01.12.2022)“…The minimum error entropy (MEE) criterion is widely used in distributed estimation, since it is insensitive to many types of non-Gaussian noises…”
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Mixture quantized error entropy for recursive least squares adaptive filtering
ISSN: 0016-0032, 1879-2693, 0016-0032Published: Elmsford Elsevier Ltd 01.02.2022Published in Journal of the Franklin Institute (01.02.2022)“… To further improve learning performance, two concepts using a mixture of two Gaussian functions as kernel functions, called mixture error entropy and mixture quantized error entropy, are proposed in this paper…”
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Kernel Risk-Sensitive Mean p-Power Error Algorithms for Robust Learning
ISSN: 1099-4300, 1099-4300Published: Basel MDPI AG 13.06.2019Published in Entropy (Basel, Switzerland) (13.06.2019)“… To address this issue, a convex kernel risk-sensitive loss (KRL) is proposed to measure the similarity in RKHS, which is the risk-sensitive loss defined as the expectation of an exponential function of the squared estimation error…”
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Quantized criterion-based kernel recursive least squares adaptive filtering for time series prediction
ISSN: 2331-8422Published: Ithaca Cornell University Library, arXiv.org 06.09.2023Published in arXiv.org (06.09.2023)“…The robustness of the kernel recursive least square (KRLS) algorithm has recently been improved by combining them with more robust information-theoretic learning criteria, such as minimum error entropy (MEE…”
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Generalized Minimum Error with Fiducial Points Criterion for Robust Learning
ISSN: 2331-8422Published: Ithaca Cornell University Library, arXiv.org 09.09.2023Published in arXiv.org (09.09.2023)“…The conventional Minimum Error Entropy criterion (MEE) has its limitations, showing reduced sensitivity to error mean values and uncertainty regarding error probability density function locations…”
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