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基于分形的音频频带盲扩展方法
  • ISSN号:1003-0530
  • 期刊名称:信号处理
  • 时间:2013
  • 页码:1127-1133
  • 分类:TN912[电子电信—通信与信息系统;电子电信—信息与通信工程]
  • 作者机构:[1]北京工业大学电子信息与控制工程学院语音与音频信号处理研究室,北京,100124
  • 相关基金:国家自然科学基金资助项目(61072089);北京市教育委员会科技发展计划重点项目(KZ201110005005)
  • 相关项目:基于非线性动力学的音频频带扩展算法研究
中文摘要:

本文提出了一种基于分形理论的音频频带盲扩展方法。首先,借助重标极差分析法估计频谱细节序列的Hurst指数,对不同音频信号谱细节序列的Hurst指数进行统计分析,验证了音频信号频域序列具有长相关特性。然后,运用坐标延迟法对谱细节序列进行相空间重构,基于夹角余弦选取预测中心相点的近邻点,根据预测中心相点和近邻相点的相关性,求取一个吸引子与预测中心相点相近的迭代函数系统,实现对高频谱细节的分形预测。最后,结合高斯混合模型的高频能量估计算法,实现宽带向超宽带的扩展算法。主、客观质量评测均表明本文算法优于传统的频带盲扩展方法。

英文摘要:

In this paper a new bandwidth extension method of audio signal based on fractal theory was proposed. Firstly, Hurst exponent of the fine spectrum was estimated by means of rescaled range analysis, and the long-range dependence of the fine spectrum was statistically verified based on Hurst exponent of the fine spectrum from different audio signals. Then, the phase space of the fine spectrum of audio signal was reconstructed by delay-coordinate method, and the neighbor phase points were selected with angle cosine. The iteration function system whose attractor was similar with the center phase point was calculated by the neighbor phase points, according to the dependency between the center phase point and the neighbor phase points. A fractal prediction model was established to recover the fine spectrum of high-frequency components of audio signals further. Finally, by combining with the high frequency energy estimation of Gaussian mixture model, the bandwidth of audio signals was extended to super-wideband from wideband. Both the objective and subjective test results demonstrate that the proposed algorithm outperforms the conventional blind bandwidth extension algorithms.

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期刊信息
  • 《信号处理》
  • 中国科技核心期刊
  • 主管单位:中国科学技术协会
  • 主办单位:中国电子学会
  • 主编:谢维信
  • 地址:北京鼓楼西大街41号
  • 邮编:100009
  • 邮箱:xhclfh@sohu.com
  • 电话:010-64010656
  • 国际标准刊号:ISSN:1003-0530
  • 国内统一刊号:ISSN:11-2406/TN
  • 邮发代号:80-531
  • 获奖情况:
  • 国家一级科技期刊
  • 国内外数据库收录:
  • 美国剑桥科学文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版)
  • 被引量:10219