应用科学学报 ›› 2018, Vol. 36 ›› Issue (4): 589-600.doi: 10.3969/j.issn.0255-8297.2018.04.003
王光艳, 耿艳香, 陈雷
收稿日期:2017-08-04
修回日期:2017-10-09
出版日期:2018-07-31
发布日期:2018-07-31
通信作者:
王光艳,副教授,研究方向:语音增强、盲语音分离,E-mail:wanggy@tjcu.edu.cn
E-mail:wanggy@tjcu.edu.cn
基金资助:WANG Guang-yan, GENG Yan-xiang, CHEN Lei
Received:2017-08-04
Revised:2017-10-09
Online:2018-07-31
Published:2018-07-31
摘要: 针对粒子群优化(particle swarm optimization,PSO)算法收敛速度慢、易陷入局部最优等缺点,提出了一种基于改进PSO算法优化的独立分量分析(independent componentanalysis,ICA)算法,用于水下语音和噪声混叠信号的盲分离.采用规范四阶累积量的绝对值作为ICA中的目标函数,通过改变惯性因子ω和压缩因子k来增强粒子的自适应寻优能力.对比实验结果表明,该算法在收敛速度、算法稳定性和分离效果方面的性能更优.
中图分类号:
王光艳, 耿艳香, 陈雷. 改进粒子群算法在水下盲语音分离中的应用研究[J]. 应用科学学报, 2018, 36(4): 589-600.
WANG Guang-yan, GENG Yan-xiang, CHEN Lei. Application Research of Improved Particle Swarm Algorithm in Underwater Speech Blind Separation[J]. Journal of Applied Sciences, 2018, 36(4): 589-600.
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