Description: 使用VB.net编写的对24位位图进行简单图像处理的程序，包括RGB与YIQ数据的相互变换，绘制亮度分布统计图，拉普拉斯滤波。
该程序是我学习图像处理算法是编写的，因此在操作界面方面的考虑较少，你可以按照以下步骤操作：选择一个文件后单击读取BMP文件，然后就可以单击“根据RGB数据绘图”，接着可以单击“RGB to YIQ”将RGB数据转化为YIQ数据，有了YIQ数据后就可以单击“绘制YIQ数据的Y分量”，对于YIQ数据，可以使用拉普拉斯滤波，然后再将Y分量显示出来-use VB.net prepared by the 24 pairs of simple bitmap image processing procedures, including RGB data and YIQ mutual transformation, mapping brightness distribution statistics, Laplace filter. The procedure to be my image processing algorithm is prepared, so that the user interface to consider the less, you can follow these steps : Select a file and click read BMP file, and then click on "RGB data mapping," and then click "RGB to YIQ "RGB data into YIQ data, with YIQ data you can click" Drawing YIQ data Y component, "for YIQ data can be used Laplace filter, and then appropriate weight displayed Y Platform: |
Size: 10282 |
Author:陈烨 |
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Description: 使用VB.net编写的对24位位图进行简单图像处理的程序，包括RGB与YIQ数据的相互变换，绘制亮度分布统计图，拉普拉斯滤波。
该程序是我学习图像处理算法是编写的，因此在操作界面方面的考虑较少，你可以按照以下步骤操作：选择一个文件后单击读取BMP文件，然后就可以单击“根据RGB数据绘图”，接着可以单击“RGB to YIQ”将RGB数据转化为YIQ数据，有了YIQ数据后就可以单击“绘制YIQ数据的Y分量”，对于YIQ数据，可以使用拉普拉斯滤波，然后再将Y分量显示出来-use VB.net prepared by the 24 pairs of simple bitmap image processing procedures, including RGB data and YIQ mutual transformation, mapping brightness distribution statistics, Laplace filter. The procedure to be my image processing algorithm is prepared, so that the user interface to consider the less, you can follow these steps : Select a file and click read BMP file, and then click on "RGB data mapping," and then click "RGB to YIQ "RGB data into YIQ data, with YIQ data you can click" Drawing YIQ data Y component, "for YIQ data can be used Laplace filter, and then appropriate weight displayed Y Platform: |
Size: 10240 |
Author:陈烨 |
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Description: 空间无线信道建模程序matlab，考虑了多径延迟，多普勒效应，信号的角度扩展（拉普拉斯分布），MIMO，可以产生MIMO信道矩阵。-Spatial channel modeling procedures matlab, taking into account multi-path delay, Doppler effect, the signal point of view the expansion of (Laplace distribution), MIMO, can generate MIMO channel matrix. Platform: |
Size: 457728 |
Author:李明 |
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Description: 用C语言编写随机信号的产生：包括均匀分布，高斯分布，二项式分布，锐利分布，
对数高斯分布，泊松分布，拉普拉斯等分布。-Using C language of the generated random signal: including uniform distribution, Gaussian distribution, binomial distribution, a sharp distribution, logarithm Gaussian distribution, Poisson distribution, Laplace distribution. Platform: |
Size: 2235392 |
Author: |
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Description: 实现一个符合Laplace分布的随机数发生器，代码完整，易于理解-The realization of a Laplace distribution in line with the random number generator, code integrity, and easy to understand Platform: |
Size: 208896 |
Author:前敏 |
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Description: 弄清楚Laplace分布形式，可以帮助我们理解Laplace分布的深刻含义-Clarify the form of Laplace distribution can help us understand the profound meaning of Laplace distribution Platform: |
Size: 143360 |
Author:xuna |
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Description: fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!.
Given the samples of a laplace distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = 1/(2*b)*exp(-abs(x-u)/b)
with parameters: u,b
format: result = fit_ML_laplace( x,hAx )
input: x - vector, samples with laplace distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
u,b - fitted parameters
CRB_b - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
- fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!.
Given the samples of a laplace distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = 1/(2*b)*exp(-abs(x-u)/b)
with parameters: u,b
format: result = fit_ML_laplace( x,hAx )
input: x - vector, samples with laplace distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
u,b - fitted parameters
CRB_b - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
Platform: |
Size: 1024 |
Author:resident e |
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Description: fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!.
Given the samples of a laplace distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = 1/(2*b)*exp(-abs(x-u)/b)
with parameters: u,b
format: result = fit_ML_laplace( x,hAx )
input: x - vector, samples with laplace distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
u,b - fitted parameters
CRB_b - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
- fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!.
Given the samples of a laplace distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = 1/(2*b)*exp(-abs(x-u)/b)
with parameters: u,b
format: result = fit_ML_laplace( x,hAx )
input: x - vector, samples with laplace distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
u,b - fitted parameters
CRB_b - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
Platform: |
Size: 1024 |
Author:resident e |
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Description: 仿真产生十种概率分布的随机序列，包括均匀分布、高斯分布、指数分布、广义指数分布、混合指数分布、韦布尔分布、瑞利分布
广义瑞利分布、拉普拉斯分布、柯西分布等，并进行参数检验，概率分布检验和独立性检验-Simulation produces ten kinds of probability distribution of random sequences, including uniform, Gaussian, exponential, generalized exponential distribution, mixed exponential distribution, Weibull distribution, Rayleigh distribution of generalized Rayleigh distribution, the Laplace distribution, Cauchy distribution etc., and parametric tests, the probability distribution of test and independence test Platform: |
Size: 2048 |
Author:高双成 |
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Description: 用逆累积分函数算出随机变量X满足拉普拉斯分布的随机数
-Random variable X is calculated using the inverse tired integral function to meet the Laplace distribution of the random number Platform: |
Size: 1024 |
Author:shenzhou |
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Description: 拉普拉斯分布的函数，官方的，，我用了很好，产生一定分布的角度
-Laplace distribution function, the official, I use a good, certain distribution angle Platform: |
Size: 1024 |
Author:recruitparade |
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Description: GA是一个参数优化算法，以编码空间代替问题的参数空间，将适应度函数作为评价依据，以编码群体为进化基础，对群体中个体遗传操作实现遗传机制，建立迭代过程，跟具体的优化对象没有直接联系，只需优化对象提供目标函数的计算标准和参数的上下限，就可得到最优结果。-the algorithm is improved by the laplace crossover in which the parent of the Laplace distribution density function coefficients replace the arithmetic crossover operator coefficients, through the parent control of offspring production. Platform: |
Size: 3072 |
Author:王斌斌 |
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Description: 实现拉普拉斯分布的参数拟合，输入一维向量即可-Achieve Laplace distribution parameter fitting, you can enter one-dimensional vector Platform: |
Size: 1024 |
Author:严肃 |
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Description: 基于3GPP 25.996 的简化SCM信道模型，可用来生成基于SCM信道的仿真实时的信道增益的产生，到达角 给出了拉普拉斯分布 均匀分布与标准的20个子径的分布三种不同的形式。-Based on 3 GPP 25.996 simplified SCM channel model, based on SCM channel can be used to generate a simulation of real-time channel gain, arrival Angle gives the Laplace distribution uniform distribution and standard 20 is a diameter of three different forms of distribution Platform: |
Size: 1024 |
Author:lqin |
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Description: 传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这
一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT)
系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表
示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的
语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优
于传统的语音增强方法。-The spectral components of speech are usually assumed to be independent in traditional short-time
spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm
with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform
(DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral
components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed
model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech
presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show
that the developed method has better noise suppression performance and lower speech distortion compared to the
traditional speech enhancement method. Platform: |
Size: 1054720 |
Author:立枣酒 |
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Description: 遗传算法的拉普拉斯交叉算子，是一个比较经典的交叉算子，现在给出它源程序-LX operator (Deep and Thakur [22]) is a self-adaptive parent cen-tric crossover operator. It makes use of Laplace distribution whosedistribution function is given by Platform: |
Size: 1024 |
Author:linxk |
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Description: 一般自然图像的梯度分布符合重尾分布，重尾分布也就是超拉普拉斯分布，根据这个特点进行图像复原。-The gradient of a natural image in line with heavy-tailed distribution, which is ultra-heavy-tailed distribution Laplace distribution, image restoration based on this feature. Platform: |
Size: 2299904 |
Author:范琳伟 |
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Search - laplace distribution