Search Results - Quantized kernel recursive minimum error entropy

  • Showing 1 - 7 results of 7
Refine Results
  1. 1

    Quantized kernel recursive minimum error entropy algorithm by Jiang, Wang, Gao, Yuyi, He, Yue, Chen, Shanmou

    ISSN: 0952-1976, 1873-6769
    Published: Elsevier Ltd 01.05.2023
    “…In this paper, we propose a online vector quantization (VQ) method based on the kernel recursive minimum error entropy (KRMEE) algorithm…”
    Get full text
    Journal Article
  2. 2
  3. 3

    Diffusion Quantized Recursive Mixture Minimum Error Entropy Algorithm by Cai, Peng, Wang, Shiyuan

    ISSN: 1549-7747, 1558-3791
    Published: New York IEEE 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…”
    Get full text
    Journal Article
  4. 4

    Mixture quantized error entropy for recursive least squares adaptive filtering by He, Jiacheng, Wang, Gang, Peng, Bei, Sun, Qi, Feng, Zhenyu, Zhang, Kun

    ISSN: 0016-0032, 1879-2693, 0016-0032
    Published: Elmsford Elsevier Ltd 01.02.2022
    Published 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…”
    Get full text
    Journal Article
  5. 5

    Kernel Risk-Sensitive Mean p-Power Error Algorithms for Robust Learning by Zhang, Tao, Wang, Shiyuan, Zhang, Haonan, Xiong, Kui, Wang, Lin

    ISSN: 1099-4300, 1099-4300
    Published: Basel MDPI AG 13.06.2019
    Published 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…”
    Get full text
    Journal Article
  6. 6

    Quantized criterion-based kernel recursive least squares adaptive filtering for time series prediction by He, Jiacheng, Wang, Gang, Zhang, Kun, Zhong, Shan, Peng, Bei

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 06.09.2023
    Published 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…”
    Get full text
    Paper
  7. 7

    Generalized Minimum Error with Fiducial Points Criterion for Robust Learning by Zhao, Haiquan, Gao, Yuan, Zhu, Yingying

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 09.09.2023
    Published 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…”
    Get full text
    Paper