河南科技学院新科学院
2014届本科毕业论文（设计）
学生姓名： 倪 闯
所在院系：新科学院电气工程系
汽油清净剂所学专业：电气工程及其自动化
霓虹灯下的哨兵剧本导师姓名： 孔晓红
完成时间：2014年4月10日
背光驱动
基于matlab自适应滤波器滤波器的设计及实现
李跃程
摘 要
自适应滤波器的研究是当今自适应信号处理中最为活跃的研究课题之一。因其具有很强的自学习、自跟踪能力和算法的简单易实现性等优点，使得它在噪化信号的检测增强，噪声干扰的抵消，通信系统的自适应均衡，图像的自适应增强复原以及未知系统的自适应参数辩识等方面都得到了广泛的应用。自适应滤波器是指利用前一时刻的结果，自动调节当前时刻的滤波器参数，以适应信号和噪声未知或随机变化的特性，得到有效的输出。研究自适应滤波器可以去除输出信号中噪声和无用信息，得到失真较小或者完全不失真的输出信号。本文介绍了自适应滤波器的理论基础，重点讲述了自适应滤波器的几种实现结构， 然后重点介绍了两种自适应滤波算法最小均方误差（LMS）算法和递推最小二乘（RLS）算法，并对LMS算法和RLS算法性能进行了详细的分析。其中LMS算法结构简单，鲁棒性强，但其收敛速度很慢，而RLS收敛速度快，但其运算量很大。最后本文对基于LMS算法和RLS算法的自适应滤波器进行MATLAB仿真应用，实验表明：在自适应信号处理中，自适应滤波信号占有很重要的地位，自适应滤波器应用领域广泛；另外LMS算法和RLS算法各有优缺点，LMS算法因其鲁棒性强特点而应用于自回归预测器，而RLS算法因其收敛速度快优点而应用于信号增强器中。 关键词：自适应滤波器，LMS算法，matlab仿真
Design and Implemeutation of the Auto-adapted Filter
Abstract
The adaptive filter is one of the most active research topic in adaptive signal processing today. Because it has a strong self-learning, self-tracking capabilities and algorithms simple ease of implementation, etc., making it in the detection in the noise of the signal enhancement, noise offset, communication systems, adaptive equalization, adaptive image enhanced recovery and unknown adaptive parameter identification have been widely used.Adaptive filter using the results of the previous time, automatically adjust the filter parameters for the current time to adapt to the characteristics of signal and noise is unknown or random variation, the effective output. Study the adaptive filter can remove noise and useless inform
刘维尔定理
ation output signal distortion smaller or completely losing the true output signal. This paper first introduces the theoretical basis of the filter, Secondly, to highlight several of the adaptive filter structure, and then focuses on two adaptive filtering algorithm minimum mean square error (LMS) algorithm and recursive least square (RLS ) algorithm, LMS algorithm simple structure, robustness, but its convergence is very slow, while the RLS convergence speed, but its computational complexity. Finally, experiments show that: MATLAB simulation applications based on the LMS algorithm and RLS adaptive filter algorithm in adaptive signal processing, adaptive filtering signal occupies a very important position in the widespread applications of adaptive filters; LMS algorithm advantages and disadvantages and RLS algorithm, LMS algorithm because of its strong robustness features used in autoregressive predictor, while the RLS algorithm is its fast convergence speed advantages applied to the signal enhancer.
s11306Keywords: adaptive filter, LMS algorithm, matlab simulation
2.4.3 自适应各型滤波器 11
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