Page 198 - 《应用声学》2023年第3期

636 2023 年 5 月

Recognition, 2002. Proceedings. 16th International Con- 2011, 23(9): 2421–2456.
ference on IEEE, 2002. [14] 李航. 统计学习方法 [M]. 北京: 清华大学出版社, 2019:
[9] 鲍长春, 白志刚. 基于非负矩阵分解的语音增强方法综述 [J]. 331–335.
信号处理, 2020, 36(6): 791–803. [15] Lee D. Algorithms for non-negative matrix factoriza-
Bao Changchun, Bai Zhigang. Speech enhancement based tion[J]. Advances in Neural Information Processing Sys-
on nonnegative matrix factorization: an overview[J]. Jour- tems, 2001: 13.
nal of Signal Processing, 2020, 36(6): 791–803. [16] 周 志 华. 机 器 学 习 [M]. 北 京: 清 华 大 学 出 版 社, 2016:
[10] Sobieraj I, Plumbley M. Coupled sparse NMF vs. ran- 121–140.
dom forest classification for real life acoustic event de- [17] Bishop C. Pattern recognition and machine learning[M].
tection[C]. Proceedings of the IEEE International Confer- New York: Springer, 2007: 338–339.
ence on Acoustics, Speech and Signal Processing (ICASSP [18] Lecun Y, Bottou L, Bengio Y, et al. Gradient-based learn-
2016), 2016. ing applied to document recognition[J]. Proceedings of the
[11] Lee D, Seung H S. Learning the parts of objects by non- IEEE, 1998, 86(11): 2278–2324.
negative matrix factorization[J]. Nature, 1999, 401(6755): [19] Zhou Y, Song S, Cheung N M. On classification of dis-
788–791. torted images with deep convolutional neural networks[J].
[12] 李乐, 章毓晋. 非负矩阵分解算法综述 [J]. 电子学报, 2008, IEEE, 2017, arXiv: 1701.01924.
36(4): 737–743. [20] Teoh A, Neo H, Ngo D. Sorted locally confined non-
Li Le, Zhang Yujin. A survey on algorithms of non- negative matrix factorization in face verification[C]. Com-
negative matrix factorization[J]. Acta Electronica Sinica, munications, Circuits and Systems, 2005. Proceedings.
2008, 36(4): 737–743. 2005 International Conference on. IEEE, 2005.
[13] Févotte C, Idier J. Algorithms for nonnegative matrix fac- [21] Huang E, Shen S. 希尔伯特 -黄变换及其应用 [M]. 张海勇,
torization with the β-divergence[J]. Neural Computation, 韩东, 王芳, 等, 译. 北京: 国防工业出版社, 2017: 4–15.