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半导体激光器低频噪声的混沌特性研究
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摘要
本论文围绕半导体激光器的低频噪声的非线性性质分析展开的。
     首先,介绍了1/f过程及小波变换的基本理论;推导了1/f过程二进制小波变换系数的相关性及其方差的特点;研究了1/f分形信号的合成方法,运用Labview模拟了低频噪声的小波变换去除白噪声的方法。重点研究了根据信号的局部奇异性和小波变换的模极大值特点进行去噪的方法。
     其次在了解了半导体激光器的低频噪声具有非线性性质之后,运用分形理论对其进行研究。多重分形谱和去趋势波动分析方法,从另外一个角度对低频噪声进行了本质分析。
     最后,首次运用混沌理论对半导体激光器的低频噪声进行分析。通过仿真和实际数据分析,提取了半导体激光器低频噪声的非线性动力学参数。研究表明,半导体激光器低频噪声的非线性动力学系统具有有限的分数维,系统的变量由有限的自由变量加以描述和生成,同时系统的Lyapunov指数为正,对系统的初始条件敏感,这些都是混沌系统的基本特征。对半导体器件的低频噪声进行了建模,并且讨论了模型的准确性和可行性。在提取其非线性动力学参数后,结合分形物理学理论,对噪声产生的机制进行了初步的探索。
In the 1960s, semiconductor laser diodes were devised, with the development of optoelectronic technology. Semiconductor lasers are widely applied in the domains of high-technology such as industry, medicine treatment, military science and information technology etc.,It is a kind of key implement in the information technique domain.The factors affecting the reliability are one of the primary sources producing low-frequency electrical noise, which intensity can reflect the quality and reliability of devices.Conventional methods for analyzing the noise based on the power spectrum in the frequency domain focus only on the whole singularity of noise signal but nelect the interior relation of time frequency.In this paper,it is researched how to use the Chaos,Fractal and other nonlinear theories on the reliability of semiconductor lasers.
     The work in this thesis is supported by the National Natural Science Foundation of China (Grant No.60471009)“Research on detection method of noise in high-power semiconductor laser diodes and their reliability correlation”and the high technology key project of Jilin province (Grant No. 20040301-4)“The quality detection and screening equipment exploitation of high-power semiconductor laser diodes”. This work is carried out mostly in detection technology of low-frequency electrical noise in LDs.
     Firstly, the production and development of semiconductor lasers is reviewed, and their application in industry, medicine treatment, military science and information technology and so on is introduced. The representation of low-frequency electrical noise used in reliability of LDs is described. And then, the application of Chaos theory in signal is discussed. And we propose the Chaos theory is applied in the noise reliability.
     Secondly, to have more detailed understanding of the noise characteristics of semiconductor lasers, the thesis introduces the components of low-frequency noise of semiconductor laser, based on the statistical properties of noise. It includes the white noise, G-R noise and 1/f noise. The sources of white noise and G-R noise are illustrated.
     Thirdly, the fundamental theories of 1/f process and wavelet transformation are introduced; the correlation and variance characteristics of binary wavelet coefficient are deduced; the methods to synthesize 1/f fractal signal are investigated, especially, the computer simulation experiments of synthesized 1/f fractal signal based on wavelet reverse transformation are carried out in detail, and other methods are also introduced; concentrating on the problems of the parameters and wave estimation for 1/f fractal signal in additive white noise background, we carry out experiment research, and the maximal likehood estimation is introduced. The simulation of 1/f noise is used by Labview.
     Forth, after nonlinear characters of low-frequency noise are confirmed, the LF noise is researched by two nonlinear methods of Chaos and Fractal. By Cao method, the accurate phase reconstruction parameters of noise are obtained. Through the simulation experiment and real-life data analysis, it is found that the calculation of correlation dimension and largest lyapunov exponent is influenced by white noise.
     Finally, the essence of semiconductor lasers noise is analyzed by Chaos and Fractal. And the model of noise is discussed. After pick-up the nonlinear dynamics parameter, we explore the mechanism of noise combined with the Fractal physics. Based on the experiment and simulation, the chaos model of semiconductor lasers’noise is proposed.
引文
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