搜索资源列表
RSNA
- 待辨识对象参数a=[1 -1.5 0.7] b=[1 0.5] 输入采用长度L=400的白噪声序列,输出 ,输入和输出数据均含不相关随机噪声,ρ(k)=1/k。利用上述递推公式,辨识系统参数。-To identify the object parameters a = [1-1.5 0.7] B = [1 0.5] Input the length L = 400 white noise sequence, the output, the input and output data
generate-white-noise-with-fpga
- 一共7篇文章,介绍了使用fpga产生任意分布白噪声的方法,值得借鉴,A total of seven articles, describes using fpga to generate arbitrary distribution of white noise, it is worth learning
RLS
- 仿真对象如下: 其中, v( k )为服从N (0,1) 分布的白噪声。输入信号u ( k) 采用M 序列,幅度为 1。M 序列由 9 级移位寄存器产生,x(i)=x(i-4)⊕x(i-9)。 选择如下辨识模型: 加权阵取Λ = I。 衰减因子β = 0.98,数据长度 L = 402。 辨识结果与理论值比较,基本相同。辨识结果可信 -he simulation object is as follows: among them, v (k) to obe
fftfast
- 基于matlab中中性定理产生的高斯白噪声的频谱自相关分-The produce white Gaussian noise spectrum based of matlab in neutral Theorem autocorrelation points
matlab
- 根据伪随机序列理论,由混合同余法产生均匀分布的随机数,进而根据中心极限定理来产生高斯噪声。 分析所产生的均匀分布和高斯分布随机信号的均值、方差、自相关等数字特征,估计其概率密度函数并进行分析,估计其功率谱密度并进行分析。说明该高斯噪声是否符合白噪声特性。 对该高斯噪声进行FIR低通滤波,估计输出低通型限带白噪声的功率谱、相关时间等,并结合白噪声通过线性系统相关理论来进行分析。 -According to the theory of pseudo-random sequence, a
msk_viterbi
- 在高斯白噪声情况下,MSK的维特比解调程序-Gaussian white noise case, the Viterbi MSK demodulation process
jiazaosheng
- 在平滑信号中加入高斯分布的白噪声,然后用db4小波函数进行多尺度分解,滤除白噪声,将滤波前后的图进行对比-Add the Gaussian distribution of the white noise in the smoothed signal, and then multi-scale decomposition db4 wavelet function, the filtered white noise, comparing before and after filtering
xiatianhe_noise
- 白噪声产生,可以进行多种分布噪声的产生,可以控制功率等。-The white noise generator, can be a variety of distribution of the generation of noise, power, etc. can be controlled.
Analysis-of-signal
- 强噪声背景下的信号处理,原信号频率是10.1,幅值0.2;噪声为标准白噪声,幅值为0.5;门限为0.65;取10次样,还原的信号频率为10.086-The signal processing in the background of strong noise, the frequency of the original signal is 10.1, amplitude 0.2 noise of the standard white noise, the amplitude is 0.5 t
yuyin
- 语音信号添加高斯白噪声 语音信号添加高斯白噪声-Add white Gaussian noise voice signal voice signal add white Gaussian noise
dsp
- 掌握功率谱估计的方法,分别产生两个零均值的白噪声数据 1 u n 和 2 u n , 其功率都为 2 0.12 u ,让 1 u n 和 2 u n 分别通过一个FIR 系统,得到输出为 1 v n 和 2 v n 。-Master power spectrum estimation method
my_hough
- 在高斯白噪声淹没的二维图像中,利用hough变换实现直线的检测。-In Gauss white noise in two-dimensional images, using Hough transform linear detection.
gaosizaosheng
- 找的别人写的一个高斯白噪声的C语言实现代码,还不错~-C language code written by someone else looking for a white Gaussian noise is also good to
小波去噪程序
- 局部放电试验所采集的信号中往往混有白噪声、周期干扰信号去除。此处采用常用db系列小波中的db6小波进行9尺度的多分辨分解后,根据白噪声能量特性,估算各尺度的阈值大小,采用硬值进行处理,后进行重构。Matlab程序如下:
jiaxingbaizaosheng
- 加性白噪声的计算机实现,我们学校老师自己编的实验指导-Additive white noise machine to achieve the guidance of our school teachers have compiled experimental
lulu_LMS
- LMS自适应滤波器做系统辨识,输入为高斯白噪声,可运行,有注释-LMS adaptive filter to do system identification, input Gaussian white noise can be run by a comment
RLS
- RLS自适应滤波器程序做系统辨识,输入为高斯白噪声,内有详细注释,可运行-RLS adaptive filter program to do system identification, the input is Gaussian white noise, with detailed notes, you can run
zaoshengchansheng
- 噪声信号产生软件,非常不错的,大家可以下载试试,一个简单产生白噪声的软件-Noise signal generator software, very good, we can try to download a simple software generates white noise
baizaosheng
- 关于白噪声的仿真程序,有功率谱及fft的变换等,很有用-About the white noise simulation program, a power spectrum and FFT transformation and so on, is very useful
self_relation
- 使用自相关方法去除信号中的高斯白噪声,提取出目标信号,对做信号处理的十分实用-Using the autocorrelation method to remove Gaussian white noise in the signal, extract the target signal, very practical to do signal processing