期刊文献+

噪声环境下语音分形特征的提取和分析 被引量:4

The Abstraction and Analysis of Fractal Characteristic of Noisy Speech
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摘要 该文针对目前的分维计算方法——盒维、关联维等精度虽高,但计算复杂,Katz维计算简单、抗噪性能好、但精度不高的现状,提出了一种改进的基于波形的算法——IBW-FD,分析了对分形布朗曲线、含噪语音(高斯白噪声,三种非平稳噪声)的性能。理论分析和实验结果表明:IBW-FD算法具有更强区分高斯白噪声和语音信号的能力;IBW-FD算法抗平稳和非平稳噪声能力要普遍好于盒维和Katz维。结果表明IBW-FD算法在复杂度、精确度和抗噪性能方面均优于现有的分维算法,是一种比较好的分维计算方法,不仅可以应用在语音处理中,而且也可应用于其它信号处理中。 According to simple computation, good anti-noise ability and low precision of Katz algorithm and complex computation and good precision of box-counting dimension and correlation dimension, an Improvement fractal algorithm Based on Wave (IBW) is presented and analyzed through the fractal Brown curve and noisy speech according to the characteristic of the box dimension and Katz dimension. The theory analyse and experiment show that IBW-FD has lower computation and higher precision than Katz dimension and box-counting dimension. IBW-FD also has stronger ability of anti-noise and distinguish Gaussian noise and speech than the others. It shows that IBW-FD is the good speech fractal algorithm because of low complexity, good precision and nice anti-noise ability.
出处 《电子与信息学报》 EI CSCD 北大核心 2007年第3期585-588,共4页 Journal of Electronics & Information Technology
基金 教育部基金(03082) 国家自然科学基金(60472058)资助课题
关键词 语音信号处理 分形维 语言增强 Speech signal processing Fractal Dimension(FD) Speech enhancement
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同被引文献34

  • 1张梅军,陈江海,侯宝科.发动机故障分形诊断中噪声信号的分析和处理[J].解放军理工大学学报(自然科学版),2006,7(4):380-384. 被引量:9
  • 2贺涛,周正欧.基于分形自仿射的混沌时间序列预测[J].物理学报,2007,56(2):693-700. 被引量:25
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