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view m-toolbox/test/test_ao_padded_sine_model.m @ 18:947e2ff4b1b9 database-connection-manager
Update plist.FROM_REPOSITORY_PLIST and plist.TO_REPOSITORY_PLIST
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
children |
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clear all; %% fs = 100; nsecs = 20; t = [0:1/fs:nsecs-1/fs]; a = ao(plist('built-in', 'padded_sine', ... 'f0', .1, ... 'Timebase', t, ... 'Tstart', 1.1, ... 'Ncycles', 2.1, ... 'phi', 90)) n = ao(plist('tsfcn', '0.1*randn(size(t))', 'fs', fs, 'nsecs', nsecs)); sw = a+n; sw.iplot %% Now try to fit this % [dc,A,f0,phi,Tstart,N] af = ao(plist('built-in', 'padded_sine', ... 'Timebase', sw, ... 'f0', .1, ... 'P', [0 1 .11 90 1 2])); iplot(sw, af) %% Now fit with simplex opts = optimset('Display', 'iter', ... 'MaxFunEvals', 10000, ... 'MaxIter', 10000, ... 'TolX', 1e-15, ... 'TolFun', 1e-15, ... 'LargeScale', 'on'); r0 = [0 1 .11 90 1 2]; mksine = @(r)(ao(plist('built-in', 'padded_sine', ... 'Timebase', sw, ... 'P', r)).y); f = @(r)(sum((mksine(r)-sw.y).^2)); % Do a few iterative fits % for kk=1:5 x0 = fminsearch(f, r0, opts); % end %% afit = ao(plist('built-in', 'padded_sine', 'Timebase', sw, 'P', x0)); iplot(sw, afit)