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Updated: Jun 28, 2025

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
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P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

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通过稀有贝叶斯学习来估计到达方向,利用低复杂度的等级优先级

Ninghui Li1, Xiaokuan Zhang2, Fan Lv1

  • 1Graduate School, Air Force Engineering University, Xi'an 710051, China.

Sensors (Basel, Switzerland)
|April 13, 2024
PubMed
概括

用于到达方向 (DOA) 估计的稀疏贝叶斯学习 (SBL) 方法使用层次先验和多个测量向量 (MMV) 的块稀疏模型来增强. 新的BSBL算法改进了稀疏信号恢复 (SSR) 并降低了复杂性.

关键词:
区块 稀疏 稀疏 的 区块来到的方向估计估计.一个有层次的先.稀疏的贝叶斯式学习.

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