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Mr. Sumon

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05 Apr 2011 RMSEARCH Randomly multiply started optimizations for global problems Author: John D'Errico

May be you are right. I know my data is noise and may model is not so perfect. If you check my data you could realize (Gaussian) that

My data-
x = 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 62, 65, 67, 70

y =
38073, 35400, 37861, 36517, 42616, 43543, 37314, 38806, 39158, 41029, 39018, 40157, 37393, 38193, 38283, 36493, 36642, 37155, 36927, 36667, 35587, 35767, 35428, 34861, 34487, 35754, 35510, 34470, 36056, 34080,
31931, 33790, 32996, 33212, 33317, 32024, 32294, 32656, 32329, 29221, 32133, 32203, 31317, 31479, 31461, 29796, 31904, 29912, 26975, 26154, 30428, 35402, 28806, 31860, 29282, 28065, 29256, 26653, 34351, 33510,
32486, 29874,

and my function -

F = 65535*(c(1)*cos(x*pi/180) + c(2)*(exp(((x*pi/180).^2)*(-log10(2))/c(3)^2))./cos(x*pi/180) + c(4))

(the constant 65535 is a guess value)Please check them and let me know your comment.

04 Apr 2011 RMSEARCH Randomly multiply started optimizations for global problems Author: John D'Errico

Dear John,
Actually I am trying to fit some data points with a model function to determine the parameter value (4 parameters). I am using lsqcurvefit function. But I am always getting "Local minimum possible" message and if I change the starting guess the result become different.
That is why I need a such algorithm which help me to determine perfect starting guess. Does your function help me?
My model is like that-
fun = @(x,xdata)x(1)*exp(-x(2)*xdata) + x(3)*exp(-x(4)*xdata);

02 Apr 2011 RMSEARCH Randomly multiply started optimizations for global problems Author: John D'Errico

I am having problem on rmsearch.m
Would please you take a look on line # 402

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