ExpSolve: Difference between revisions
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Revision as of 08:19, 11 July 2011
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expSolve
Purpose
Solve exponential fitting problems for given number of terms p.
Calling Syntax
Prob = expAssign( ... );
Result = expSolve(Prob, PriLev); or
Result = tomRun('expSolve', PriLev);
Description of Inputs
Prob.SolverL2||Name of solver to use. If empty, TOMLAB selects dependent on license.Prob | Problem created with expAssign. |
PriLev | Print level in tomRun call. |
Description of Outputs
Result TOMLAB | Result structure as returned by solver selected by input argument Solver. |
LS | Statistical information about the solution. See Table 153, page 239. |
Global Parameters Used
Description
expSolve solves a cls (constrained least squares) problem for exponential fitting formulates by expAssign. The problem is solved with a suitable or given cls solver.
The aim is to provide a quicker interface to exponential fitting, automating the process of setting up the problem structure and getting statistical data.
M-files Used
GetSolver, expInit, StatLS and expAssign
Examples
Assume that the Matlab vectors t, y contain the following data:
To set up and solve the problem of fitting the data to a two-term exponential model
,
give the following commands:
>> p = 2; % Two terms >> Name = 'Simple two-term exp fit'; % Problem name, can be anything >> wType = 0; % No weighting >> SepAlg = 0; % Separable problem >> Prob = expAssign(p,Name,t,y,wType,[],SepAlg); >> Result = tomRun('expSolve',Prob,1); >> x = Result.x_k' x = 0.01 0.58 72.38 851.68
The vector contains the parameters as so the solution may be visualized with
>> plot(t,y,'-*', t,x(3)*exp(-t*x(1)) + x(4)*exp(-t*x(2)) );
Figure 6: Results of fitting experimental data to two-term exponential model. Solid line: final model, dash-dot: data.