摘要
依据非线性动力学理论,在音频信号的修正离散余弦变换(MDCT)域,采用自相关法和虚假近邻法(FNN)分别计算延迟时间和嵌入维数,重构出音频信号MDCT域信息的相空间,并基于Rosen-stein小数据量法计算最大Lyapunov(李雅普诺夫)指数,依据其正负对音频频域序列的混沌特性进行了统计分析和验证。实验表明,音频信号MDCT序列的最大Lyapunov指数皆为正,音频信号具有混沌特性。
According to the nonlinear dynamics theory, the phase space of MDCT （Modified Discrete Cosine Transform） coefficients of audio signals is reconstructed by computing delay time and embedding dimension in terms of autocorrelation method and false nearest neighbor （FNN） method, respectively. The maximum Lyapunov exponents are computed by means of Rosenstein small data sets method. The chaotic characteristic of audio signals in frequency domain is statistically analysed and verified based on the sign of the maximum Lyapunov exponents. The experiments show that the maximum Lyapunov exponents are almost positive for the MDCT series of audio signals, which demonstrates that the audio signals have the chaotic characteristics.
出处
《电讯技术》
北大核心
2011年第7期97-102,共6页
Telecommunication Engineering
基金
国家自然科学基金资助项目(61072089
60872027)
北京市自然科学基金资助项目(4082006)
北京市属高等学校人才强教计划
北京工业大学国家大学生创新性实验项目(101000506)~~
关键词
音频信号处理
修正离散余弦变换
相空间重构
LYAPUNOV指数
混沌特性
audio signal processing
modified discrete cosine transform（MDCT）
phase space reconstruction
Lyapunov exponent
chaotic characteristic
