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自治混沌系统中抗噪声干扰的频率检测模型
引用本文:舒娜,张晓星,孙才新. 自治混沌系统中抗噪声干扰的频率检测模型[J]. 重庆大学学报(自然科学版), 2013, 36(6): 148-153
作者姓名:舒娜  张晓星  孙才新
作者单位:重庆大学 输配电装备及系统安全与新技术国家重点实验室,重庆 400044;重庆大学 输配电装备及系统安全与新技术国家重点实验室,重庆 400044;重庆大学 输配电装备及系统安全与新技术国家重点实验室,重庆 400044
基金项目:国家重点基础研究发展计划资助项目(973项目:2009CB724506)。
摘    要:提出一种用自治混沌系统检测受到噪声干扰的信号频率的方法,将含有噪声干扰的信号加入到自治混沌系统的某一项,再给受扰系统施加一个状态负反馈,通过适当地调节反馈增益将受扰系统的轨道控制到系统的某一个极限环,然后利用循环相态技术,统计一定时间内轨道定向穿过某一个平面的次数,由固定的时间内得到周期的个数进而确定系统的振荡频率。由于系统的频率由待测信号的频率决定,而不受噪声的影响,所以待测信号的频率也就是系统的振荡频率。仿真实验结果进一步验证了该方法的有效性。

关 键 词:自治混沌系统  负反馈  振荡频率  信号检测  Lyapunov指数

The frequency detection model with anti-noise in the autonomous chaotic system
SHU N,ZHANG Xiaoxing and SUN Caixin. The frequency detection model with anti-noise in the autonomous chaotic system[J]. Journal of Chongqing University(Natural Science Edition), 2013, 36(6): 148-153
Authors:SHU N  ZHANG Xiaoxing  SUN Caixin
Affiliation:State Key Laboratory of Power Transmission Equipment & System Security and New Technology of Chongqing University, Shapingba District, Chongqing 400044, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology of Chongqing University, Shapingba District, Chongqing 400044, China;State Key Laboratory of Power Transmission Equipment & System Security and New Technology of Chongqing University, Shapingba District, Chongqing 400044, China
Abstract:A method of detecting the signal frequency which is disturbed by the noise based on the autonomous chaotic system is proposed. A signal with noise was added to an autonomous chaotic system, and then a negative feedback was imposed to it. The feedback gain was appropriately adjusted, so as to let the noisy system orbit be a limit cycle. The number of times that the orbit went directly through a plane was calculated by loop phase technology, and the vibration frequency was found according to it. The frequency of system is determined by the frequency of the test signal, yet free from noise, so the frequency of the test signal is the vibration frequency of the system. Simulation results further demonstrate the effectiveness of the method.
Keywords:autonomous chaotic system   negative feedback   vibration frequencies   signal detection   lyapunov index
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