Search - p laplace

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[Other] DSPPrograms DL : 0: DSP编程常用函数 double uniform(double a,double b,long int* seed) double gauss(double mean,double sigma,long int *seed) double exponent(double beta,long int *seed) double laplace(double beta,long int* seed) double rayleigh(double sigma,long int *seed) double weibull(double a,double b,long int*seed) int bn(double p,long int*seed) int bin(int n,double p,long int*seed) int poisson(double lambda,long int *seed) void dft(double x[],double y[],double a[],double b[],int n,int sign) void fft(double x[],double y[],int n,int sign)-DSP programming functions commonly used double uniform (a double, double b, long int * seed) double Gauss (double mean, double sigma, long int * seed) double exponent (double beta, long int * seed) double Laplace (double beta, * long int seed) double Rayleigh (double sigma, long int * seed) double Weibull (a double, double b, long int * seed) int bn (double p, long int * seed) int bin (int n, p double, seed long int *) int poisson (double lambda, long int * seed) void dft index (double x [], double y [], [] a double, double b [], int n, int sign) void fft (double x [], double y [], int n, int sign)
Update : 2008-10-13 Size : 2.16kb Publisher : 山城棒棒儿军
[Special Effects] Criminisi算法 DL : 3: 改进了Criminisi算法，采用P-laplace算子作为数据项进行优先级计算，并有计算PSNR的功能-Improved Criminisi algorithm, using P-laplace operator as data items priority basis, and have calculated the functions of PSNR
Update : 2011-05-05 Size : 4.57kb Publisher : aqlkui@aqtc.edu.cn
[Other] DSPPrograms DL : 0: DSP编程常用函数 double uniform(double a,double b,long int* seed) double gauss(double mean,double sigma,long int *seed) double exponent(double beta,long int *seed) double laplace(double beta,long int* seed) double rayleigh(double sigma,long int *seed) double weibull(double a,double b,long int*seed) int bn(double p,long int*seed) int bin(int n,double p,long int*seed) int poisson(double lambda,long int *seed) void dft(double x[],double y[],double a[],double b[],int n,int sign) void fft(double x[],double y[],int n,int sign)-DSP programming functions commonly used double uniform (a double, double b, long int* seed) double Gauss (double mean, double sigma, long int* seed) double exponent (double beta, long int* seed) double Laplace (double beta,* long int seed) double Rayleigh (double sigma, long int* seed) double Weibull (a double, double b, long int* seed) int bn (double p, long int* seed) int bin (int n, p double, seed long int*) int poisson (double lambda, long int* seed) void dft index (double x [], double y [], [] a double, double b [], int n, int sign) void fft (double x [], double y [], int n, int sign)
Update : 2025-02-19 Size : 2kb Publisher : 山城棒棒儿军
[Documents] gansehtu DL : 1: 研究了基于块填充的图像修复算法,修复图像的质量容易受到待修复区域边界像素修复顺序的影响,通过分析待修复区域像素点所在模块的图像特征,改进了填充算法的优先权, 分别是基于P-Laplace算子和Euler’s elastica模型的优先权计算方法的改进。实验结果证实了文中所介绍算法能有效提高重建图像的感知质量。 -Studied the block-based image restoration algorithm for filling, repair image quality to be susceptible to repair regional border pixels to repair the effects of the order, by analyzing the pixel region to be repaired where the module
Update : 2025-02-19 Size : 1.51mb Publisher : 陈建军
[Special Effects] PicStudio DL : 0: 对二维码图像处理，对图像进行SOBEL、Laplace等边缘检测处理方法，对图像波形进行分析，找出图像的极限点，是一款非常不错图像处理程序。-this is image deal software
Update : 2025-02-19 Size : 45kb Publisher :
[3D Graphic] Laplace-Gaussian-Pyramid DL : 0: ffdhfhg b fjiogn soonsnvjv fin f fdg josg-fdgdsdffdfgfgkio p p d
Update : 2025-02-19 Size : 2kb Publisher : gygy
[Special Effects] p-laplace DL : 0: 改进了Criminisi算法，采用P-laplace算子作为数据项进行优先级计算，并有计算PSNR的功能-Improved Criminisi algorithm, using P-laplace operator as data items priority basis, and have calculated the functions of PSNR
Update : 2025-02-19 Size : 6kb Publisher : yorksue
[matlab] fit_ML_laplace DL : 0: 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
Update : 2025-02-19 Size : 1kb Publisher : resident e
[matlab] fit_ML_log_normal DL : 0: 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
Update : 2025-02-19 Size : 1kb Publisher : resident e
[Other] 619 DL : 0: C THE INVERSE LAPLACE TRANSFORM OF 1/(P**2+1) IS COMPUTED C FOR T=0.1,1,2,3,4,5,10,20,30,40,50,60,70,80,90 AND 100 C (THESE VALUES ARE STORED IN THE ARRAY TVAL). C THE REQUESTED TOLERANCES ARE EPSAB=EPSRE=1.0D-4, 1.0D-8 C AND 1.0D-12 (THESE VALUES ARE STORED IN THE ARRAY E) C THE EXACT INVERSE LAPLACE TRANSFORM IS SIN(T). C ALSO THE EXACT ERROR IS COMPUTED -C THE INVERSE LAPLACE TRANSFORM OF 1/(P**2+1) IS COMPUTED C FOR T=0.1,1,2,3,4,5,10,20,30,40,50,60,70,80,90 AND 100 C (THESE VALUES ARE STORED IN THE ARRAY TVAL). C THE REQUESTED TOLERANCES ARE EPSAB=EPSRE=1.0D-4, 1.0D-8 C AND 1.0D-12 (THESE VALUES ARE STORED IN THE ARRAY E) C THE EXACT INVERSE LAPLACE TRANSFORM IS SIN(T). C ALSO THE EXACT ERROR IS COMPUTED
Update : 2025-02-19 Size : 6kb Publisher : wubangyu