代码搜索:solves

找到约 1,488 项符合「solves」的源代码

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m pfminlcon.m

function [X,FVAL,EXITFLAG,OUTPUT] = pfminlcon(FUN,initialX,Aineq,Bineq,Aeq,Beq,LB,UB,options) %PFMINLCON Finds a linearly constrained minimum of a function. % PFMINLCON solves problems of the form
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m find_params.m

function out=find_params(TFS,HS) % function out=find_params(TFS,HS) % % This function solves (if possible) the values for symbolic parameters in HS. % Basicly this function is about solving a syst
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cpp gradebook.cpp

// Fig. 4.9: GradeBook.cpp // Member-function definitions for class GradeBook that solves the // class average program with counter-controlled repetition. #include using std::cout; us
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java finaloverridingillusionex.java

// reusing/FinalOverridingIllusionEx.java // TIJ4 Chapter Reusing, Exercise 20, page 269 // Show that the @Override annotation solves the problem in ths section import static net.mindview.util.Prin
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m mst_k.m

%MST_k.m %This program solves the Minimum Spanning Tree problem by using Kruskal Algorithm.') n=input('Enter the vertices number of the graph:n= ') W=input('Enter the weight adjacent matrix of the
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m rwg3.m

%RWG3-FREQUENCY LOOP % Calculates the impedance matrix using function IMPMET % and solves MoM equations. % Takes into account lumped elements (L, C, R) - antenna load % Uses the mesh fil
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m nlsqold.m

function [x,OPTIONS,CostFunction,JACOB] = nlsqold(FUN,x,OPTIONS,GRADFUN,varargin) %NLSQ Solves non-linear least squares problems. % NLSQ is the core code for solving problems of the form: % min
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java finaloverridingillusionex.java

// reusing/FinalOverridingIllusionEx.java // TIJ4 Chapter Reusing, Exercise 20, page 269 // Show that the @Override annotation solves the problem in ths section import static net.mindview.util.Prin
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m rwg3.m

%RWG3-FREQUENCY LOOP % Calculates the impedance matrix using function IMPMET % and solves MoM equations. % Takes into account lumped elements (L, C, R) - antenna load % Uses the mesh fil
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m fps.m

function u = fps(p, isSlope, dx, dy) % fps -- Fast Poisson solver with boundary values. % fps(p) solves laplacian(u) = p for u, assuming the % boundary values are given along the perimeter of %