代码搜索：Gradient

找到约 2,951 项符合「Gradient」的源代码

代码结果 2,951
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/216626/4889581

bas_fun rectangle.rt.1.bas_fun

4 1 0 0.0 -1.0 1 0 0 0 ./rectangle.RT.1.bas_fun.so lambda_1 gradient_lambda_1 1 1 1.0 0.0 1 0 0 0 ./rectangle.RT.1.bas_fun.so lambda_2 gradient_lambda_2 1 2 0.0 1.0 1 0 0 0 ./rectangle.RT.1.ba
·
www.eeworm.com/read/216626/4889590

bas_fun four_tetrahedron.1.bas_fun

7 0 0 0.0 0.0 0.0 1 0 0 0 0 ./four_tetrahedron.1.bas_fun.so lambda_1 gradient_lambda_1 0 1 1.0 0.0 0.0 1 0 0 0 0 ./four_tetrahedron.1.bas_fun.so lambda_2 gradient_lambda_2 0 2 0.0 1.0 0.0 1 0 0 0
·
www.eeworm.com/read/216626/4889600

bas_fun four_tetrahedron.1.d.bas_fun

4 3 0 0.0 0.0 0.0 1 0 0 0 0 ./four_tetrahedron.1.D.bas_fun.so lambda_1 gradient_lambda_1 3 0 1.0 0.0 0.0 1 0 0 0 0 ./four_tetrahedron.1.D.bas_fun.so lambda_2 gradient_lambda_2 3 0 0.0 1.0 0.0 1 0
·
www.eeworm.com/read/389321/8533632

m mkramp.m

% IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN) % % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) % containing samples of a ramp function, with given gradient DIRECTIO
·
www.eeworm.com/read/397477/8043482

m modskew.m

function [chm, snrk] = modskew(ch,sk,p); % Adjust the sample skewness of a vector/matrix, using gradient projection, % without affecting its sample mean and variance. % % This operation is not an ort
·
www.eeworm.com/read/331444/12828240

m mkramp.m

% IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN) % % Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar) % containing samples of a ramp function, with given gradient DIRECTION %
·
www.eeworm.com/read/101039/6260180

jbx compierecolor.jbx

[PropertyInfo] flat,boolean,false,false, , ,true, flatColor,Color,false,false, , ,true, gradient,boolean,false,false, , ,true, gradientLowerColor,Color,false,false, , ,t
·
www.eeworm.com/read/234502/14110953

1st readme.1st

GRADIENT VECTOR FLOW DEMONSTRATION USING MATLAB Chenyang Xu and Jerry Prince Image Analysis and Communications Laboratory Johns Hopkins University June 17, 1997, updated on September 9, 1999
·
www.eeworm.com/read/233016/14173608

m bpdn_obj.m

function [obj,grad,hess] = FnameBPDN( x ) % [obj,grad,hess] = FnameBPDN( x ) % computes the objective value, gradient and diagonal Hessian % of the linear function lambda e'x, where la
·
www.eeworm.com/read/224369/14595526

m sep96.m

% sep96.m implements the learning rule described in Bell \& Sejnowski, Vision % Research, in press for 1997, that contained the natural gradient (w'w). % % Bell & Sejnowski hold the patent for this le
·