74 lines
1.4 KiB
Matlab
74 lines
1.4 KiB
Matlab
function [val_ar t_ar f_val_ar] = AR_estimate( t, val, freq, nu, mu, expand_factor)
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% [val_ar t_ar f_val_ar] = AR_estimate( t, val, freq, < nu, mu, expand_factor >)
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%
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% apply autoregressive signal model to improve dft results
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%
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% t : time vector
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% val : time domain values
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% freq : frequency vector for dft
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%
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% optional
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% nu : AR order (default 40)
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% mu : number of timesteps to train the model (default 3*nu)
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% expand_factor : increase signal length by this factor (default 5)
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%
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%
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% openEMS matlab interface
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% -----------------------
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% Author: Thorsten Liebig, 2011
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%
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% See also ReadUI, DFT_time2freq
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if numel(t) ~= numel(val)
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error 'numel(t) ~= numel(val)'
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end
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if (nargin<4)
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nu = 40;
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end
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if (nargin<5)
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mu = 3*nu;
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end
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if (nargin<6)
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expand_factor=5;
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end
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if (mu<=2*nu)
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error 'mu should be larger than 2*nu'
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end
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if (expand_factor<=1)
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error 'expand_factor must be larger than 1'
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end
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dt = t(2)-t(1);
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M = numel(t);
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if (M<0.6*mu)
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error 'signal is to short for AR estimate --> decrease AR order'
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end
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for n=1:mu-nu
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b(n) = val(end-n+1);
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for m=1:nu
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A(n,m)=val(end-n+1-m);
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end
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end
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a = ((A'*A)\A')*b';
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val_ar = val;
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t_ar = t;
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for k=M:expand_factor*M
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val_ar(k) = 0;
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t_ar(k) = t_ar(k-1)+dt;
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val_ar(k) = sum(a.*val_ar(k-(1:nu))');
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end
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if (max(val_ar(M:end)) > max(val))
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error 'estimated signal appears to be unstable --> use a larger mu'
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end
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f_val_ar = DFT_time2freq(t_ar, val_ar, freq);
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