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auxiliary-variables
- 用辅助变量法递推算法估计模型的参数.辅助变量估计是在模型误差为相关噪声的情况下通过引入辅助变量矩阵对线性最小二乘估计的一种改进。 -Recursive algorithm to estimate model parameters using instrumental variables method. Auxiliary variables is estimated that in the case of the model error is related to an improveme
deconvolution
- 采用FIR最小二乘逆滤波器来实现反卷积 1.通过输入信号xn与传递函数gn求输出yn 2.通过使平方误差达到最小求出最佳延迟 3通过最佳延迟求得逆滤波器传递函数hn 4通过hn与yn进行卷积运算得到还原的输入信号xn1，进行对比 5按照题设要求，进行相关噪声添加，再次进行上述实验过程 -Using least squares FIR inverse filter to achieve deconvolution
EigValAnly_CohandIncoh_Noise
- 阵列接收空间相关和不相关噪声的特征值分析-Eigen value anlysis for incoherent and Coherent noise in Array signal Processing
GP
- 基于贝叶斯理论的高斯过程代码，包含高斯过程回归分析，以及相关噪声处理和高斯过程分类，提供数据进行测试，-Gauss procedure code based on Bayesian theory, including Gaussian process regression analysis, and related processing and noise Gaussian process classification, to provide data for testing, etc.
test3
- 1）产生高斯白噪声； 2）产生高斯色噪声； 3）产生高斯谱相关对数正态分布随机序列； 4）对产生的上述随机序列进行功率谱估计； 5）对产生的上述随机序列进行概率密度函数估计。(Generating a Gaussian spectral correlation logarithmic normal distribution random sequence;)
How_to_generate_AWGN_noise
- 关于高斯白噪声系数生成，以及所需服从高斯分布的伪随机序列的相关文档，对于产生高斯白噪声的过程详细给出，希望对你的学习有所帮助(About Gauss white noise coefficient generation, as well as the need to obey the Gauss distribution pseudo random sequence of relevant documents, for the production of Gauss white noise pr
homework1
- 此程序用于产生零均值单位方差高斯白噪声的1000个样点，并利用周期图法和平均周期图法进行自相关的估计。(This program is used to produce 1000 sample points under the distribution of zero mean unit variance of Gaussian white noise , and the Periodogram method and average cycle diagram method are used t
8
- 加性噪声相关时带乘性噪声系统的最优估计(when the additive noise related systems with multiplicative noise estimation)
program
- 本程序通过自相关方法处理含有噪声的信号中，信噪比可达-20dB(The noise in the signal is filtered by the method of word correlation)
直方图相关系数
- 可以用来评价两幅图像灰度图直方图的相关度，得到结果可以用来分析有噪声和无噪声图像的不同(Can be used to evaluate the histogram correlation of two image grayscale histograms, and the results can be used to analyze the difference between noisy and noiseless images)
kalman滤波相关矩阵
- kalman滤波效果矩阵，状态阵，噪声驱动阵等(gn,fn,and are all about kalman filter)
现代信号处理
- 产生高斯白噪声和均匀分布白噪声，并且分析了对信号的基本处理的相关函数等基本函数(Gaussian white noise and evenly distributed white noise are generated, and basic functions such as correlation functions for basic processing of signals are analyzed.)
music改进算法
- 一种基于信号子空间和噪声子空间的music改进算法(An improved music algorithm based on signal subspace and noise subspace)
workspace
- 用matlab进行含噪声的语音信号滤波，实现相关功能，仅供参考(Using matlab to carry out noisy speech signal filtering, realize relevant functions, for reference only.)
code
- 噪声背景下的信号检测是一项复杂而又重要的任务，在雷达信号检测和通信领域都是重要的课题。在低信噪比情况下与普通自相关函数法进行了比较。给出了时域及频域(Signal detection in noisy background is a complex and important task. It is an important topic in the field of radar signal detection and communication. Compared with the gene
bt
- 通过周期图法、自相关法等计算高斯白噪声的功率谱(The power spectrum of Gauss white noise is calculated by periodogram and autocorrelation method.)
代码
- 实现了一个基于 matlab 的信号发生器，并同时画出了信号的时域表示，自相关函数及功率谱，实现的信号发生器能够产生的信号为： （1） 白噪声 （2） 单位冲激信号 （3） 正弦信号 （4） 方波信号 （5） 三角波信号(A signal generator based on MATLAB is realized, and the time domain representation, autocorrelation function and power spectrum of the sign
gaosi
- 采用直接法或间接法（通过自相关函数）编制matlab程序，计算信号cos（2πf1t）+cos（2πf2t）叠加高斯白噪声后的功率谱密度。(Matlab program is compiled by direct method or indirect method (through autocorrelation function) to calculate the power spectral density of signal cos (2 PI f1t) +cos (2 PI f2t) s
White_PinkNoise
- 构造均匀白噪声、服从高斯分布的白噪声及粉红噪声，并得到它们的自相关函数、功率谱密度等(Constructing uniform white noise, white noise obeying Gauss distribution and pink noise, and obtaining their autocorrelation function, power spectral density, etc.)
噪声分析
- 正态分布、均匀分布随机噪声分析，通过画出正态分布、均匀分布随机噪声的频谱、功率谱、一维概率密度、自相关函数对噪声进行分析。(Random Noise Analysis of Normal Distribution)