Zhongming Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Zhongming Wang has a total of 23 co-authors. Here are the top co-authors by number of shared publications:
- Guomin Yang
Singapore Management University
2 shared publications - Biwen Chen
Chongqing University, Chongqing, China
1 shared publication - Changsong Jiang
University of Electronic Science and Technology of China
1 shared publication Hongyang Yan
Guangzhou University
1 shared publication- Jin Li
Department of Orthopedics, No. 1 Orthopedics Hospital of Chengdu, 389 Jinhui Road, Chengdu, 610031, China, 86 02886635247
1 shared publication Lin Lou
Department of Biomedical Engineering, Urumchi General Hospital of Lanzhou Military Region, Xinjiang, 830000, China
1 shared publication
Latest Publications
- 1 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Forensics and Security
- Vol. 21, 9495-9510
STEAD: Subversion-Resistant Portable Encrypted Data Deduplication With File Sharing
- 1 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Forensics and Security
- Vol. 21, 9495-9510
STEAD: Subversion-Resistant Portable Encrypted Data Deduplication With File Sharing
- 2 November 2021
- Published by Springer Nature
- p. 3-18
Public Key Based Searchable Encryption with Fine-Grained Sender Permission Control
- 2 November 2021
- Published by Springer Nature
- p. 3-18
Public Key Based Searchable Encryption with Fine-Grained Sender Permission Control
- 1 August 2015
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 30, 1956-1960
Speech enhancement based on the Wiener filter and wavelet entropy
Because of constant noise estimations, the speech enhancement of standard Wiener filters is poor under varied noise environments. In the present study, we propose an improved Wiener filter method for speech enhancement based on wavelet entropy. Wavelet entropy (WE) point detection can discriminate between speech activity segments and noise segments. This discrimination provides a basis through which noise can be estimated and updated accurately, leading to accurate a priori signal-to-noise ratios obtained from updated noise estimations, reduction of residual musical noise, and enhancement of speech signals degraded by non-uniform noise. Spectrogram comparisons of enhanced speech signals between the proposed WE Wiener filter and a standard Wiener filter show that the former is better at suppressing non-uniform noise than the later. Their perceptual evaluation of speech quality measures also show that the WE Wiener filter yields better enhanced speech quality than the standard Wiener filter.
- 1 August 2015
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 30, 1956-1960
Speech enhancement based on the Wiener filter and wavelet entropy
Because of constant noise estimations, the speech enhancement of standard Wiener filters is poor under varied noise environments. In the present study, we propose an improved Wiener filter method for speech enhancement based on wavelet entropy. Wavelet entropy (WE) point detection can discriminate between speech activity segments and noise segments. This discrimination provides a basis through which noise can be estimated and updated accurately, leading to accurate a priori signal-to-noise ratios obtained from updated noise estimations, reduction of residual musical noise, and enhancement of speech signals degraded by non-uniform noise. Spectrogram comparisons of enhanced speech signals between the proposed WE Wiener filter and a standard Wiener filter show that the former is better at suppressing non-uniform noise than the later. Their perceptual evaluation of speech quality measures also show that the WE Wiener filter yields better enhanced speech quality than the standard Wiener filter.