[PDF][PDF] 基于终止准则改进K-SVD 字典学习的稀疏表示特征增强方法
王华庆， 任帮月， 宋浏阳， 董方， 王梦阳 - 机械工程学报, 2019 - qikan.cmes.org
针对传统K 奇异值分解(K-Singular value decomposition, K-SVD) 算法在稀疏表示过程中,
由于目标信号稀疏度难以确定以及字典原子受噪声干扰大导致稀疏表示效果较差的问题 …
由于目标信号稀疏度难以确定以及字典原子受噪声干扰大导致稀疏表示效果较差的问题 …
[PDF][PDF] Sparse representation method based on termination criteria improved K-SVD dictionary learning for feature enhancement
王华庆， 任帮月， 宋浏阳， 董方… - Journal of Mechanical …, 2019 - qikan.cmes.org
A sparse representation method based on VMD and termination criteria improved K-SVD
dictionary learning algorithm is proposed to solve the issues about the choice of signal …
dictionary learning algorithm is proposed to solve the issues about the choice of signal …