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# Steepest Decent Method for Multiple Variable Functions 1.0

Date Added: April 07, 2013  |  Visits: 224

Replace your function in the code and the output will be similar to the followingSteepest Descent Method=============Function = -(3*x1+x2+6*x1*x2-2*(x1^2)+2*(x2^2))Hessian...... [ 4 -6] [ ] [-6 -4]Gradient...... [-3 - 6 x2 + 4 x1] [ ] [-1 - 6 x1 - 4 x2]Eigen Values[ 2*13^(1/2), 0][ 0, -2*13^(1/2)] f(x0)=5.000000_________________________________________Iteration = 1Gradient of X0 -7 5X0 = -1 0X0 - alpha. gradient(X0) = -1+7*alpha -5*alpha f(X0 - alpha. gradient(X0)) =3-16*alpha+30*(-1+7*alpha)*alpha+2*(-1+7*alpha)^2-50*alpha^2 diff(f(X0 - alpha. gradient(X0)))/diff alpha =-74+516*alpha alphaval = 37/258 alphaval2 = 0.143410852713178x1 = 0.003875968992248 -0.717054263565892f(x2)=-0.306202_________________________________________Iteration = 2Gradient of X1 1.317829457364341 1.844961240310078X1 = 0.003875968992248 -0.717054263565892X1 - alpha. gradient(X1) = 1/258-170/129*alpha -185/258-238/129*alpha f(X1 - alpha. gradient(X1)) =91/129+748/129*alpha-6*(1/258-170/129*alpha)*(-185/258-238/129*alpha)+2*(1/258-170/129*alpha)^2-2*(-185/258-238/129*alpha)^2 diff(f(X1 - alpha. gradient(X1)))/diff alpha =-85544/16641-4624/129*alpha alphaval = -37/258 alphaval2 = -0.143410852713178

 Requirements: No special requirements Platforms: Matlab Keyword: 0143410852713178x1,  0717054263565892x1,  1844961240310078x1,  Alpha,  Alpha Alpha Alpha Alpha Alpha,  Alphaval,  Difffx,  Gradient,  Gradientx,  Gradientx Diff,  Iteration Users rating: 0/10