Sparsity promoted non-negative matrix factorization for source separation and detection

Yanlin Wang,Yun Li,K. C. Ho,Alina Zare,Marjorie Skubic

DSP（2014）

引用 4|浏览10

暂无评分

摘要

The effectiveness of non-negative matrix factorization (NMF) depends on a suitable choice of the number of bases, which is often difficult to decide in practice. This paper imposes sparseness on the factorization coefficients in order to determine the number of bases automatically during the decomposition process. The benefit of sparse promotion for NMF is demonstrated through application to sound source separation as well as acoustic-based human fall detection under strong interference.

查看译文

关键词

nonnegative matrix factorization coefficients,sound source separation,decomposition process,nmf,elder care,source separation,acoustic signal detection,acoustic-based human fall detection,matrix decomposition,source detection,non-negative matrix factorization,sparse promotion,interference,interference (signal)

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要