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author | harpreet | 2016-04-16 12:12:15 +0530 |
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committer | harpreet | 2016-04-16 12:12:15 +0530 |
commit | 10e2e4d8b4a7592a8631ddac8e8d1664d6f0b9e3 (patch) | |
tree | 087af3ca1853d01afef58684b09b537597317023 /tests/general_tests/lsqnonlin/lsqnonlin_ub2.sce | |
parent | 8484c85784b84cc3a9257f8d8065b3a8a7800628 (diff) | |
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fmincon examples
Diffstat (limited to 'tests/general_tests/lsqnonlin/lsqnonlin_ub2.sce')
-rw-r--r-- | tests/general_tests/lsqnonlin/lsqnonlin_ub2.sce | 32 |
1 files changed, 32 insertions, 0 deletions
diff --git a/tests/general_tests/lsqnonlin/lsqnonlin_ub2.sce b/tests/general_tests/lsqnonlin/lsqnonlin_ub2.sce new file mode 100644 index 0000000..2206b2f --- /dev/null +++ b/tests/general_tests/lsqnonlin/lsqnonlin_ub2.sce @@ -0,0 +1,32 @@ +// Check for elements in ub + +function y=yth(t, x) +y = x(1)*exp(-x(2)*t) +endfunction +// we have the m measures (ti, yi): +m = 10; +tm = [0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5]'; +ym = [0.79, 0.59, 0.47, 0.36, 0.29, 0.23, 0.17, 0.15, 0.12, 0.08]'; +// measure weights (here all equal to 1...) +wm = ones(m,1); +// and we want to find the parameters x such that the model fits the given +// data in the least square sense: +// +// minimize f(x) = sum_i wm(i)^2 ( yth(tm(i),x) - ym(i) )^2 +// initial parameters guess +x0 = [1.5; 0.8]; +// in the first examples, we define the function fun and dfun +// in scilab language +function y=myfun(x, tm, ym, wm) +y = wm.*( yth(tm, x) - ym ) +endfunction + +lb = [0 0] +ub = [10] + +//Error +//lsqnonlin: The Upper Bound is not equal to the number of variables +//at line 252 of function lsqnonlin called by : +//[xopt,resnorm,residual,exitflag,output,lambda,gradient] = lsqnonlin(myfun,x0,lb,ub) + +[xopt,resnorm,residual,exitflag,output,lambda,gradient] = lsqnonlin(myfun,x0,lb,ub) |