wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual demopt1 wolffd@0: wolffd@0: wolffd@0: wolffd@0:

demopt1 wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Demonstrate different optimisers on Rosenbrock's function. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

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wolffd@0: demopt1
wolffd@0: demopt1(xinit)
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wolffd@0: Description wolffd@0:

wolffd@0: The four general optimisers (quasi-Newton, conjugate gradients, wolffd@0: scaled conjugate gradients, and gradient descent) are applied to wolffd@0: the minimisation of Rosenbrock's well known `banana' function. wolffd@0: Each optimiser is run for at most 100 cycles, and a stopping wolffd@0: criterion of 1.0e-4 is used for both position and function value. wolffd@0: At the end, the trajectory of each algorithm is shown on a contour wolffd@0: plot of the function. wolffd@0: wolffd@0:

demopt1(xinit) allows the user to specify a row vector with wolffd@0: two columns as the starting point. The default is the point [-1 1]. wolffd@0: Note that the contour plot has an x range of [-1.5, 1.5] and a y wolffd@0: range of [-0.5, 2.1], so it is best to choose a starting point in the wolffd@0: same region. wolffd@0: wolffd@0:

wolffd@0: See Also wolffd@0:

wolffd@0: conjgrad, graddesc, quasinew, scg, rosen, rosegrad

wolffd@0: Pages: wolffd@0: Index wolffd@0:

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