代码搜索：parameter
找到约 10,000 项符合「parameter」的源代码
代码结果 10,000
www.eeworm.com/read/464675/7067484
m fitting.m
function [Fy a]=Fitting(x,y,n)
%curve fitting, y=f(x)
%Fy is the estimation of y at x
%a is the coefficients of poly
%n is the order
%Weight w==1;
n1=n+1;
Fy=zeros(n1,1);
Lox=length(x);
%Aa=
www.eeworm.com/read/322305/7072508
m hyppdf.m
function y=hyppdf(x,alpha,beta,delta,mu);
%HYPPDF Hyperbolic probability density function (pdf).
% Y=HYPPDF(X,ALPHA,BETA,DELTA,MU) returns the pdf of the hyperbolic
% distribution with shape p
www.eeworm.com/read/322305/7072514
m hypcdf.m
function y=hypcdf(x,alpha,beta,delta,mu,starti);
%HYPCDF Hyperbolic cumulative distribution function (cdf).
% Y=HYPCDF(X,ALPHA,BETA,DELTA,MU,STARTI) returns the cdf of the hyperbolic
% distri
www.eeworm.com/read/322305/7072533
m nigcdf.m
function y=nigcdf(x,alpha,beta,delta,mu,starti);
%NIGCDF NIG cumulative distribution function (cdf).
% Y=NIGCDF(X,ALPHA,BETA,DELTA,MU,STARTI) returns the cdf of the NIG
% distribution with sha
www.eeworm.com/read/322305/7072534
m nigpdf.m
function y=nigpdf(x,alpha,beta,delta,mu);
%NIGPDF NIG probability density function (pdf).
% Y=NIGPDF(X,ALPHA,BETA,DELTA,MU) returns the pdf of the NIG
% distribution with shape parameter ALPHA
www.eeworm.com/read/299984/7140053
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/299984/7140368
m ldc.m
%LDC Linear Bayes Normal Classifier (BayesNormal_1)
%
% [W.R,S,M] = LDC(A,R,S,M)
% W = A*LDC([],R,S,M);
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/462042/7211859
txt 代码27-22.txt
warning('MATLAB:paramAmbiguous', ...
'Ambiguous parameter name, "%s".', param) % param为变量
www.eeworm.com/read/461403/7228025
m wrimage.m
function x = wrimage(DataOut,h,w,filename,PicExpand)
%WRIMAGE Formats the data and writes it to a bmp file
%
% x = wrimage(DataOut,h,w,filename,PicExpand)
% x : image data as a single row vector.