基于duffing混沌振子的毕业设计.doc

湖 北 民 族 学 院 毕业论文（设计） 基于duffing振子和小波变换的微弱信号检测方法研究 学生姓名： 学 号： 系 别： 电气工程系 专 业： 电子信息科学与技术 指导教师： 评阅教师： 论文答辩日期 答辩委员会主席 摘 要 现代社会中到处充斥着电子产品，它们为我们的生活带来了方便，但同时，大量产品的出现导致我们现在生活在嘈杂的噪声环境中。也为我们在进行地震监测等一系列微弱信号检测的工作带来了不便。本论文的主要研究方向就是利用混沌系统和小波变换的相关方法来检测藏匿在强噪声背景下的微弱信号。 在论文最开头介绍了混沌系统和小波去噪的有关定义，就此内容介绍了它们在现阶段国内外的研究现状。小波变换的多分辨率特点能够很好地帮助我们看到信号的局部特性，将含有噪声的信号分解成若干层，对每层进行不同的阀值选取后可以得到相对应的小波系数，从而能够重构出特性很好的信号。将得到的信号作为驱动力输入混沌系统。基于混沌理论的混沌系统状态的判别依据。根据相轨迹的图像变化来找到系统的临界阀值点。 本论文使用的方法改善了传统的微弱信号检测技术，使得实验结果的性能得到了很大的提升。通过使用本论文介绍的方法得到了噪声背景下的微弱正弦信号，小波去噪后信号得到了很好的提取。 关键字：微弱信号，混沌系统，小波变换，相轨迹 Abstract Modern society is full of electronic products, they are for the convenience of our lives. while at the same time , The emergence of a large number of products that we are now live in the noisy environment. which make it difficulty for us to detect weak sign such as the seismic signal. The main research direction of this paper is to use the method of chaotic system and wavelet transform to detect weak signal hiding under strong noise background. At the beginning of this paper, introduces the definition in the chaotic system and wavelet denoising, then is the last research status on them at home and abroad. The wavelet transform can be very good to help us see the local characteristic of signal, signal containing noise is decomposed into several layers, each layer of different threshold selection can be obtained after wavelet coefficients corresponding to reconstruct the signal characteristics, which would be very good. At last , The resulting signal will used as the driving force input of the chaotic system. On the basis of basis of distinguishing the state of chaotic system based on chaos theory. In order to find the critical threshold point of the system, we should according to the change of phase trace image . This paper uses improved weak signal detection technology, properties of the experimental results has been greatly improved.