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自适应滤波器的LMS算法的仿真
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自适应滤波器的LMS算法的仿真
摘要本文主要介绍自适应滤波器的LMS算法及其仿真。在一些无法预知信号和噪声特性的场合,无法使用具有固定滤波器系数的滤波器对信号实现最优滤波,,使自适应滤波器在工作环境变化时自动调节其单位脉冲响应特性,提出了一种自适应算法:最小均方算法(LMS算法)。根据LMS算法性能特点,在MATLAB环境下编写了基于LMS算法的有限长自适应滤波器的程序,仿真其收敛性能。。理论分析和仿真结果表明,所设计的自适应滤波器具有快速的跟踪能力和收敛性能,且稳态误差较小.
关键词 LMS算法;自适应滤波器;MATLAB
Simulation of Adaptive Filter Based on LMS Algorithms
Abstract Adaptive filter’s LMS algorithms and simulation are mainly introduced in this paper ,In some occasions which isn’t predict signal and noise characteristics ,no method which use fixed filter coefficient can achieve optimal filtering signal and the only solution is introduction of the adaptive filter. In order to achieve the optimum filtering effect,making the adaptive filter can adjust its units impulse response characteristics automatically when the working environment is paper presents a kind of adaptive algorithm :Least Mean Square(LMS algorithm).According to the character of LMS algorithm. We can write the finite LMS algorithm of adaptive filter’s program with MATLAB and its convergence performance can be simulated. the designed filter is used to plish the filter of sine wave which are disturbed by white noise .Adaptive filter have system identification and separation role. The conclusion from the theoretic analysis and simulation show that, the designed filter has fast track and convergence capability along with small steady state error.
Keywords LMS algorithms; Adaptive Filter; MATLAB
前言
滤波器可以分为经典滤波器和现代滤波器两大类。经典滤波器是假定输入信号x(n)中的有用成分和希望去掉的成分各占有不同的频带, 即关于信号和噪声应具有一定的先验知识, 这样当原始信号通过一个线性系统时无用的成分就可以滤掉。如果有用信号和噪声的频谱相互重叠, 那么通过经典滤波器就无法去除噪声或干扰。而现代滤波器就能够解决上述问题。现代滤波器是把信号和噪声都视为随机信号, 利用它们的统计特征(如自相关函数、功率谱等) 导出一套最佳的估计算法, 然后用硬件或软件予以实现。自适应滤波器就属于现代滤波器。
随着信号处理学科领域理论与技术的不断进步,自适应信号处理已成为信号与信息处理学科的重要分支,并在诸如通信、雷达、声纳、工业控制、地震勘探及生物医学工程等领域获得越来越广泛的应用[2]。自适应功能根据输入数据调整滤波器中自由参数来实现。从而是得自适应滤波器是非线性的。我们说自适应滤