Scholarlink

<p>This article develops a censored regression tensor least mean-square (CR-TLMS) algorithm, which first rectifies the sample selection bias for censored measurement, and then implements the tensor decomposition of two low-dimensional components to estimate the weight vector. In addition, the algorithm’s mean convergence is derived, and the steady-state mean-square error performance of CR-TLMS is derived. Numerical experiments under censored measurement environments corroborate the accuracy of theoretical findings and the superior capability of the proposed algorithm.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Tensor Decomposition-Based Censored Regression Adaptive Filtering Algorithm

  • 期刊论文

  • 发表日期：

    2025年4月5日

查看全文
  • Tao Yu,
  • Binyu Wang,
  • Xiang Li,
  • Yi Yu

摘要

This article develops a censored regression tensor least mean-square (CR-TLMS) algorithm, which first rectifies the sample selection bias for censored measurement, and then implements the tensor decomposition of two low-dimensional components to estimate the weight vector. In addition, the algorithm’s mean convergence is derived, and the steady-state mean-square error performance of CR-TLMS is derived. Numerical experiments under censored measurement environments corroborate the accuracy of theoretical findings and the superior capability of the proposed algorithm.