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Volterra_MultiStepPred_luzhenbo
- 基于Volterra滤波器混沌时间序列多步预测 作者：陆振波，海军工程大学 欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页 电子邮件：luzhenbo@sina.com 个人主页：luzhenbo.88uu.com.cn 参考文献： 1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlineariti
MATLAB_Arithmetic
- 一个matlab实现IIR、FIR、LMS、NLMS等算法的m代码-a Matlab IIR, FIR, LMS, NLMS algorithm code m
FIR-differentiate
- By building a nonlinear function relationship between an d the error signal，this paper presents a no— vel variable step size LMS(Least Mean Square)adaptive filtering algorithm．
firbynna
- 此程序为本人编写的神经网络法设计1型FIR滤波器的程序，读者读此程序后，可以很深刻地理解如何用BP网络和LMS算法来设计滤波器。 只需更改程序中的H值，即可生成各种低通，高通，带通，带阻滤波器。程序运行结果可得到滤波器系数，幅频曲线和衰减曲线。 可通过更改迭代步长和误差极限来调整滤波器特性。
adaptivefir
- 自适应滤波器。自适应滤波器为11个权系数的FIR结构。（1）不同的方差σ2（2）LMS算法画出一次实验的误差平方收敛曲线，训练长度为500，给出滤波器系数；进行20次独立实验，给出平均收敛曲线。不同步长值的比较。（3）RLS算法，LMS和RLS算法的比较 -Adaptive filter. Adaptive filter weights for 11 of the FIR structure. (1) different variance σ2 (2) LMS algorithm for a
zero_tap_detection_adaptiveequalizer
- 具有检测FIR滤波器单位脉冲响应h[n]中零系数（zero tap detection）功能的LMS算法自适应均衡器，可处理相关输入（colored inputs)和独立输入(white inputs). 检测出零系数的个数和位置,减少后续计算次数，提高算法效率。-Zero Tap Detection LMS adaptive Equalizer with Tap Decoupling techniques and Colored Inputs and white inputs.
lms
- 均方误差最小LMS算法，s为一个wav格式的音频文件。FIR滤波器长度为5。-LMS
LMS-AR
- 本程序利用自适应LMS算法实现FIR最佳维纳滤波器。可用于观察影响自适应LMS算法收敛性，收敛速度以及失调量的各种因素-This procedure using adaptive LMS algorithm is optimal FIR Wiener filter. Can be used to observe the impact of adaptive LMS algorithm convergence, convergence speed and the amount of imbalan
ale
- 提供自适应线谱增强函数。结合LMS算法和自适应滤波来实现线谱增强。实现受白噪声 (mu,sigma)污染的单频信号(frequency f)的增强。-function to perform adaptive line enhancement using LMS algorithm and an adaptive FIR filter。 ALE concept enhances a single tone signal (frequency f) affected by white noise (
lsm
- 数字信号处理 传统的宽带信号中抑制正弦干扰的方法是采用陷波器(notch filter),为此我们需要精确知道干扰正弦的频率.然而当干扰正弦频率是缓慢变化时,且选频率特性要求十分尖锐时,则最好采用自适应噪声抵消的方法.下图是用一个二阶FIR的LMS自适应滤波器消除正弦干扰的一个方案。-DSP
LMS-algorithm-
- 自适应滤波器是一种参数可自适应调整的有限冲激响应(FIR)数字滤波器，具有非递归结构形式。介绍了自适应滤波器的基本原理，用LMS自适应算法来仿真，得到LMS算法在自适应滤波中的收敛特性。-Adaptive filter is an adaptive adjustment of parameters can be finite impulse response (FIR) digital filter, with a non-recursive structure. Describes the b
10.1.1.11.5905
- This paper compares performance of nite impulse response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square(LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation resul
LMS
- Simple function to adjust filter coefficients using the LMS algorithm adjusts filter coefficients, b, to provide the best match between the input, x(n), and a desired waveform, d(n),both waveforms must be the same length, uses a standard FIR filter
code
- FIR 滤波器的自适应模拟，通过收敛性、学习曲线等方面对RLS 算法以及LMS 算法的不同特性进行了比较-FIR Filter simulation, through the convergence of the learning curve compared with the RLS algorithm, as well as the different characteristics of the LMS algorithm
LMS
- 用matlab实现LMS自适应算法，20阶的fir滤波器，自适应效果非常好。-Matlab LMS adaptive algorithm, two order of fir filter, the adaptive effect is very good.
levinson
- 图1为均衡带限信号所引起失真的横向或格型自适应均衡器(其中横向FIR系统长M=11), 系统输入是取值为±1的随机序列，其均值为零；参考信号；信道具有脉冲响应： 式中用来控制信道的幅度失真(W = 2～4, 如取W = 2.9,3.1,3.3,3.5等)，且信道受到均值为零、方差(相当于信噪比为30dB)的高斯白噪声的干扰。试比较基于下列几种算法的自适应均衡器在不同信道失真、不同噪声干扰下的收敛情况(对应于每一种情况,在同一坐标下画出其学习曲线): 1）横向/格-梯型结构LMS算法
ANC
- 自适应滤波LMS算法实现有源噪声消除：Mtalab程序；FLMS算法-Application Program to Test Active Noise Controla 32-tap adaptive FIR filter is used to produce an anti-noise to cancel the primary noise. The adaptive algorithms used here are the filtered-x LMS (FXLMS) and normali
adsp
- Using LMS Algorithm, elimination random noise ECG signal. peak voltage of the signal is 3.5 millivolts and length of the ECG Signal is 2700. FIR system to be identified 31 order-Using LMS Algorithm, elimination random noise ECG signal. peak voltage
lms
- 自适应滤波辨识系统，使用LMS算法构建自适应滤波器，外加一篇文章。-use 500 iterations of an adapting filter system to identify and unknown 32-nd order FIR filter
LMS_FIR
- fir结构的lms算法，可用于噪声消除，参数估计(The LMS algorithm of fir structure can be used for noise elimination and parameter estimation)