Description: 自己编写的比较全面的故障诊断matlab函数程序，包括统计法、时域法、时间序列法、频谱及功率普密度函数、小波分析法程序中有详细的说明。-their preparation of a more comprehensive fault diagnosis Matlab function procedures, including statistics, time domain, time series, and power spectral density function Pronk, wavelet analysis procedures are described in detail. Platform: |
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Author:suzhixiao |
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Description: 基于matlab的信号时频分析仿真
MATLAB 软件在多个研究领域都有着广泛的应用。其中,它的频谱分析和滤波器的分析设计功能很强,从而使数字信号处理变得十分简单、直观。本文介绍了时频分析基础理论及一些应用,运用MATLAB 语言实现了旨在构造一种时间和频率的密度函数,以揭示信号中所包含的频率分量及其演化特性的wigner-ville 分布。-Matlab-based time-frequency signal analysis and simulation software MATLAB in a number of research fields as wide Pan application. Among them, its spectrum analysis and the analysis of filter design function very strong, so that the digital signal processing is very simple. intuitive. This paper presents a time-frequency analysis of basic theory and some applications, use MATLAB to the structure of a time and frequency density function, to reveal the signal contained in the frequency components and evolution of the air to air-ville distribution. Platform: |
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Author: |
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Description: 本文的题目是改进的粒子滤波在组合导航中的应用研究。文档可用caj打开。
本课题首先研究了GPS/DR车载定位系统的组合模型，然后在分析了非线性滤波的基础上，引入了粒子滤波。粒子滤波是一种基于递推计算的序列蒙特卡罗算法，它采用一组从概率密度函数上随机抽取的并附带相关权值的粒子集来逼近后验概率密度，从而不受非线性、非高斯问题的限制。虽然粒子滤波存在诸多优点，然而它仍然存在诸如粒子数匿乏、滤波性能不高、实时性差等问题。-The title of this article is to improve the particle filter in the navigation of the applied research. CAJ can be used to open the document. This issue initially on the GPS/DR Vehicle Location System portfolio model, and then the analysis of nonlinear filtering based on the introduction of a particle filter. Particle filter is a recursive calculation based on Sequential Monte Carlo algorithm, it uses a set of probability density function from random samples and weights attached to the relevant set of particles to approximate a posteriori probability density, and thus not subject to non-linear, the issue of non-Gaussian constraints. Although there are many advantages of particle filter, yet it still exists, such as particle number Punic poor, filter performance is not high, real-time poor. Platform: |
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Author:阳关 |
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Description: Parzen窗函数概率密度估计演示程序
完全按照《现代模式识别》孙即祥著作 2.4.4《动态聚类法》算法3实现
使用欧式距离作为测度标准。-Parzen window probability density function is estimated demo program in full accordance with the Platform: |
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Author:潘水洋 |
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Description: 提出了一种新的连续型隐马尔可夫模型(HMM ) 的概率密度函数, 并导出了一系列的参
数寻优迭代公式,-A new Continuous Hidden Markov Model (HMM) of the probability density function, and derived a series of parameters optimization iteration formula, Platform: |
Size: 178176 |
Author:杨絮 |
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Description: 应用Parzen窗法估计样本的概率密度函数；
估计样本为标准正态分布和均匀分布；-Application of Parzen window method estimates the probability density function of the sample estimated sample standard normal distribution and uniform distribution Platform: |
Size: 1024 |
Author:张刚 |
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Description: 大津阈值分割法，也称最大类间方差法，利用图像的灰度分布密度函数定义图像的交叉熵。
交叉熵可看作是两个概率系统（即图像背景及目标）的信息量之间的差异。求出的交叉熵越大，则分割效果越好。
-Otsu threshold segmentation method, also known as Otsu method, the use of gray-scale image distribution density function definition images of cross-entropy. Cross-entropy can be seen as both the probability of system (that is, the image background and objectives) the difference between the amount of information. Obtained the greater the cross-entropy, then partition the better. Platform: |
Size: 1024 |
Author:Mingruixia |
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Description: 对图像进行中值金字塔分解后，分别求取各层的概率密度函数-Image after median pyramid decomposition, respectively, to strike all floors of the probability density function Platform: |
Size: 181248 |
Author:tony |
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Description: parzen窗法，功能是根据样本进行概率密度函数估计。实现了对正态分布概率密度函数和均匀分布双峰概密函数进行估计-Parzen window method, function is based on a sample of the estimated probability density function. The realization of the normal distribution probability density function and uniform distribution Bimodal density function is estimated over Platform: |
Size: 3072 |
Author:陈坚 |
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Description: ERF函数的原代码,erf(x)=(2/根号下派)*(exp(-z方)对z积分，积分下限是0，上限是x)，误差函数从形式上很像正态分布的分布函数Φ(x)，是对一个形如正态分布的概率密度函数做变上限积分的结果；
-ERF function of the original code, erf (x) = (2/root allocation under No.)* (exp (-z side) of the z integral, integral lower limit is 0, the upper limit is x), error function from the form like normal distribution distribution function Φ (x), is a shape such as the normal distribution probability density function do change the results limit points Platform: |
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Author:zhanghua |
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Description: Mean Shift 这个概念最早是由Fukunaga等人[1]于1975年在一篇关于概率密度梯度函数的估计中提出来的,其最初含义正如其名,就是偏移的均值向量,在这里Mean Shift是一个名词,它指代的是一个向量,但随着Mean Shift理论的发展,Mean Shift的含义也发生了变化,如果我们说Mean Shift算法,一般是指一个迭代的步骤,即先算出当前点的偏移均值,移动该点到其偏移均值,然后以此为新的起始点,继续移动,直到满足一定的条件结束.
用matlab实现mean shift算法仿真-Mean Shift the concept was first used by Fukunaga et al [1] in 1975 in an article on the probability density function estimation of gradient raised its original meaning, as its name implies, is the offset of the mean vector, where is the Mean Shift a noun, it refers to a vector, but with the Mean Shift the development of the theory, Mean Shift the meaning has changed, if we say that Mean Shift algorithm, generally refers to an iterative steps, namely, first calculate the current point Mean offset, move the shift points to its average, and then as a new starting point and continue to move until the end to meet certain conditions. realize using mean shift algorithm matlab simulation Platform: |
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Author:maolei |
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Description: L3_1.m: 純量量化器的設計(程式)
L3_2.m: 量化造成的假輪廓(程式)
L3_3.m: 向量量化器之碼簿的產生(程式)
L3_4.m: 利用LBG訓練三個不同大小與維度的碼簿並分別進行VQ(程式)
gau.m: ML量化器設計中分母的計算式(函式)
gau1.m: ML量化器設計中分子的計算式(函式)
LBG.m: LBG訓練法(函式)
quantize.m:高斯機率密度函數的非均勻量化(函式)
VQ.m: 向量量化(函式)
L3_2.bmp: 影像檔
lena.mat: Matlab的矩陣變數檔
-L3_1.m: scalar quantizer design (the program) L3_2.m: quantitative result of the false contour (the program) L3_3.m: Vector quantizer code book of the generation (the program) L3_4.m: training in the use of LBG three different size and dimension of the code book and separate VQ (program) gau.m: ML quantizer design in the denominator of the calculation formula (function) gau1.m: ML quantizer design in the calculation of molecule-type ( function) LBG.m: LBG training method (function) quantize.m: Gaussian probability density function of the non-uniform quantization (function) VQ.m: vector quantization (function) L3_2.bmp: image file lena.mat: Matlab matrix variable file Platform: |
Size: 191488 |
Author:Oki |
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Description: ex6_1 ～ ex6_3二项分布的随机数据的产生
ex6_4 ～ ex6_6通用函数计算概率密度函数值
ex6_7 ～ ex6_20常见分布的密度函数
ex6_21 ～ ex6_33随机变量的数字特征
ex6_34 采用periodogram函数来计算功率谱
ex6_35 利用FFT直接法计算上面噪声信号的功率谱
ex6_36 利用间接法重新计算上例中噪声信号的功率谱
ex6_37 采用tfe函数来进行系统的辨识，并与理想结果进行比较
ex6_38 在置信度为0.95的区间上估计有色噪声x的PSD
ex6_39 在置信度为0.95的区间上估计两个有色噪声x，y之间的CSD
ex6_40 用程序代码来实现Welch方法的功率谱估计
ex6_41 用Welch方法进行PSD估计，并比较当采用不同窗函数时的结果
ex6_42 用Yule-Walker AR法进行PSD估计
ex6_43 用Burg算法计算AR模型的参数
ex6_44 用Burg法PSD估计
ex6_45 比较协方差方法与改进的协方差方法在功率谱估计中的效果
ex6_46 用Multitaper法进行PSD估计
ex6_47 用MUSIC法进行PSD估计
ex6_48 用特征向量法进行PSD估计-ex6_1 ~ ex6_3 binomial distribution of the generated random data
ex6_4 ~ ex6_6 generic function value of the probability density function
ex6_7 ~ ex6_20 common distribution density function
ex6_21 ~ ex6_33 figure characteristics of random variables
periodogram function ex6_34 used to calculate the power spectrum
ex6_35 direct method using FFT signal above the noise of the power spectrum
ex6_36 recalculated using the indirect method on the example of the power spectrum of noise signal
tfe function ex6_37 used for system identification, and results were compared with the ideal
ex6_38 at 0.95 confidence interval for the estimated colored noise x on the PSD
ex6_39 at 0.95 confidence interval of the two colored noise on the estimated x, y between the CSD
ex6_40 code used to achieve the Welch method of power spectrum estimation
Welch method ex6_41 with PSD estimates, and compare different window function when the results when
ex6_42 using Yule-Walker AR method is esti Platform: |
Size: 7168 |
Author:张满超 |
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Description: 该算法是经典的信噪比估计算法——最大似然估计算法，利用接收信道的先验概率密度函数，ML法能够很好的估计信号的信噪比-The algorithm is a classic signal to noise ratio estimation algorithm- maximum likelihood estimation algorithm, using the a priori receiver channel probability density function, ML method can be a very good signal to noise ratio is estimated Platform: |
Size: 1024 |
Author:贾小勇 |
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Description: 本实验要求根据课本中给出的高斯噪声和椒盐噪声的概率分布的形状和参数编写两个通用程序分别给一个图像中添加高斯噪声和椒盐噪声。高斯噪声是n维分布都服从高斯分布的噪声，椒盐噪声是图像中经常见到的一种噪声是一种随机的黑点或者白点。在实验中通过它们对应的概率密度函数得到噪声分布函数进而与原图像进行叠加产生出对应的噪声图像-Textbooks in this experiment are given under the Gaussian noise and salt and pepper noise in the shape of the probability distribution and parameters of common procedures for the preparation of the two images were added to a Gaussian noise and salt and pepper noise. Gaussian noise is subject to the distribution of n-dimensional Gaussian noise, salt and pepper noise is often the image to see a noise is a random white spots or black spots. In the experiment through their corresponding probability density function of the noise distribution function to be the original image superimposed with the corresponding noise generated image Platform: |
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Author:jhm |
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Description: （一）目的：通过对常用的概率密度函数和分布函数的应用，达到熟练掌握概率密度函数和分布函数调用方法的目的。
（二）任务：对实际的案例进行分析，调用相应概率密度函数和分布函数，使用MATLAB软件计算其结果。
（三）要求：理解概率密度函数和分布函数，能够解决实际问题。
-(A) Purpose: used by the probability density function and distribution function of the application, to master the probability density function and distribution methods of the purpose of function call. (B) tasks: the actual analysis of the case, call the corresponding probability density function and distribution function, the use of MATLAB software to calculate their results. (C) requirements: understanding of the probability density function and distribution function, to solve practical problems. Platform: |
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Author:猫猫 |
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Description: 基于小波包分解的语音去噪，根据熵谱概率密度函数估计阈值，去除实际环境噪声。-Based on wavelet packet decomposition of the voice de-noising, in accordance with spectral entropy probability density function estimated threshold, the actual removal of environmental noise. Platform: |
Size: 1024 |
Author:djf |
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Description: 用monte carlo的方法对Nakagami的概率密度函数进行仿真-Using monte carlo methods for Nakagami probability density function of the simulation Platform: |
Size: 1024 |
Author:于 |
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Description: 通过matlab代码画出的各种概率密度函数图形仅供参考-By matlab code to draw the beta probability density function graph for reference only Platform: |
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Author:王伟 |
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Description: The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov
model (HMM). Consider there are n states in the HMM. The particular isolated
speech signal is divided into finite number of frames. Every frame of the speech
signal is assumed to be generated from any one of the n states. Each state is modeled as the multivariate Gaussian density function with the specified mean vector
and the covariance matrix. Let the speech segment for the particular isolated word
is represented as vector S. The vector S is divided into finite number of frames
(say M). The i th frame is represented as Si . Every frame is generated by any of the n
states with the specified probability computed using the corresponding multivariate
Gaussian density model. Platform: |
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Author:Khan17
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Search - MATLAB density function