Optimizing unknown function with incomplete set of variables.

[hale812]

I am building a set of filters combined in a circuit with no explicit
relation for cut-off frequencies.

Instead, I am building a cost function F with a set of parameters F(var1,
var2, freq1, freq2,....)
Basically, the cost F is a sum of all partial costs univariate of partial
filters by the *absolute* value. F=∑(|Fi|). So I expect the problem converge
with F=0|Fi=0.

freq1, freq2 and everything coming after them are CONSTANTS passed by a
problem generator.

var1, var1 are to be found.
It is possible to guess initial values of var1 and var2 basing on partial
analysis of F components.

I am stuck with Octave standard tool set. Seems like most tools treat
strictly canonical polynomial problems, simple first-order sum of scalars.
There is minimization tool that treat F(x) with x as all-variables vector.

And I did not find a way to optimize/minimize/ my problem with both
variables and constants passed to F.

Can you please help me with a way to solve this?



--
View this message in context: 
http://octave.1599824.n4.nabble.com/Optimizing-unknown-function-with-incomplete-set-of-variables-tp4681123.html
Sent from the Octave - General mailing list archive at Nabble.com.