代码搜索：descent

找到约 1,131 项符合「descent」的源代码

代码结果 1,131
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m descent.m

% Animation for steepest descent, Newton, and LM directions % % Roger Jang, June 9, 1996 obj_fcn = 'paraf'; % a parabolic surface obj_fcn = 'banana'; % banana function obj_fcn = 'hyperf'; % a
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www.eeworm.com/read/467198/7020219

m descent.m

% Animation for steepest descent, Newton, and LM directions % % Roger Jang, June 9, 1996 obj_fcn = 'paraf'; % a parabolic surface obj_fcn = 'banana'; % banana function obj_fcn = 'hyperf'; % a
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www.eeworm.com/read/143498/12870881

m descent.m

% Animation for steepest descent, Newton, and LM directions % % Roger Jang, June 9, 1996 obj_fcn = 'paraf'; % a parabolic surface obj_fcn = 'banana'; % banana function obj_fcn = 'hyperf'; % a
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www.eeworm.com/read/105661/15661959

gif descent.gif

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www.eeworm.com/read/191902/8417184

m newton_descent.m

function Min = Newton_descent(a, theta, fun) % Minimize a function using the Newton descent algorithm % % Inputs: % a - Initial search point % theta - Convergence criterion % fun - The fun
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www.eeworm.com/read/191902/8417221

m gradient_descent.m

function Min = gradient_descent(a, theta, eta, fun) % Minimize a function using the basic gradient descent algorithm % % Inputs: % a - Initial search point % theta - Convergence criterion %
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www.eeworm.com/read/288304/8643700

asv steepest_descent.asv

function [v, w]= steepest_descent(rp) % function [v, w]= steepest_descent(rp) % % computes trajectories of the steepest descent algorithm % it requires the passing of a structure that contains a
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www.eeworm.com/read/288304/8643708

m steepest_descent.m

function [v, w]= steepest_descent(rp) % function [v, w]= steepest_descent(rp) % % computes trajectories of the steepest descent algorithm % it requires the passing of a structure that contains a
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www.eeworm.com/read/286662/8751801

m newton_descent.m

function Min = Newton_descent(a, theta, fun) % Minimize a function using the Newton descent algorithm % % Inputs: % a - Initial search point % theta - Convergence criterion % fun - T
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www.eeworm.com/read/286662/8751832

m gradient_descent.m

function Min = gradient_descent(a, theta, eta, fun) % Minimize a function using the basic gradient descent algorithm % % Inputs: % a - Initial search point % theta - Convergence criterion
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