摘要
基于对低信噪比下状态空间重构问题的研究,并结合重构信号强度(RSS)方法分析重构窗口,得到明显改善信噪比的重构状态空间.进而在低信噪比下,利用改进后的最大李雅普诺夫(Lyapnuov)指数的算法有效地估计出Lorenz等模型的最大李雅普诺夫指数.这种方法可能成为识别淹没在噪声中的混沌信号的有效途径.
Based on the research of state space reconstruction at poor SNR and the analysis of reconstruction window using the method of reconstruction signal strength (RSS), state space reconstruction with improved SNR is derived. From this,the largest Lyapunov exponents of Lorenz and Rossler attractor are estimatedeffectively at poor SNR by use of a improved algorthm of the largest Lyapunov exponent. This method may become an effective approach to distinguish the chaotic signals overwhelmed in the noise.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1997年第10期102-106,共5页
Acta Electronica Sinica
基金
国防预研基金