期刊文献+

语音信号同伦非线性模型分析理论与算法 被引量:1

HOMOTOPY NONLINEAR MODELING FOR SPEECH SIGNALS
下载PDF
导出
摘要 提出了一种基于同伦理论的语言信号非线性模型分析理论与算法,具有计算量小、稳定性强、收敛性好等一般非线性模型分析方法所没有的优点,同时保持了线性模型的简单性与通用性. Based on the homotopy theory, this paper presents a novel nonlinear modeling method for speech signals, the homotopy nonlinear modeling method (HNMM). Unlike the ordinary nonlinear modeling methods, the HNMM is robust and easy to compute, and has very good convergence property. Besides, the HNMM is nearly as simple as the traditional linear modeling methods and thus can be used very extensively. The validity of the HNMM has been proved by experimental results.
出处 《自动化学报》 EI CSCD 北大核心 1997年第2期201-206,共6页 Acta Automatica Sinica
基金 国家自然科学基金 国家教委博士点基金 广东省自然科学基金
关键词 语音信号 建模 非线性模型 算法 Speech signal modeling, nonlinearity, homotopy theory.
  • 引文网络
  • 相关文献

参考文献3

  • 1韦岗,神经网络模型.学习及应用,1994年
  • 2张丽清,Numer Math,1993年,65卷,523页
  • 3朱雪龙,语音信号数字处理(译),1983年

同被引文献5

  • 1Aapo Hyvarinen,Juha Karhunen,Erkki Oja.Independent Component Analysis[M].A Wiley-Interscience Publication.JOHN WILEY&SONS,INC.2001.
  • 2A Cichocki,R Thawonmas.On-line algorithm for blind signal extraction of arbitrarily distributed,but temporally correlated sources using second order statistics[J].Neural Processing Letters,2000,12(1):91-98.
  • 3夸特尔瑞.离散时间语音信号处理:原理与应用[M].赵胜辉,译.北京:电子工业出版社,2004.
  • 4Yang H H,Amari S.Adaptive on-line learning for blind separation-maximum entropy and minimum mutual information[J].Neural Computation,1997,9:1457-1482.
  • 5A Cichocki,S Amari.Adaptive blind signal and image processing:learning algorithm and pplications[M].Chichester,England:John Wiley,2002.

引证文献1

相关主题

;
使用帮助 返回顶部