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annotate m-toolbox/test/LTPDA_training/topic5/TrainigSession_T5_Ex02.m @ 7:1e91f84a4be8 database-connection-manager

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Make ltpda_up.retrieve work with java.sql.Connection objects
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % Training session Topic 5 exercise 02
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 % System identification in z-domain 2
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4 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % 1) Load fsdata object from file
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % 2) Fit loaded TF data with zDomainFit and fixed order
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % 3) Compare results
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % L FERRAIOLI 22-02-09
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10 %
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11 % $Id: TrainigSession_T5_Ex02.m,v 1.3 2009/02/25 18:18:45 luigi Exp $
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12 %
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13 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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14
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 %% 1) load fsdata
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16
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17 % load AO from file
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18 rfilt = ao(plist('filename', 'topic5\T5_Ex02_rfilt.xml'));
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19 iplot(rfilt)
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20
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 %% 2) Fitting TF - fixed model order
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22
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % Loaded fsdata are the response of an order 19 partial fractioned filter.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % We now try to fitting the loaded filter response with zDomainFit with a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 % fixed model order.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 % We set Autosearch to off, in this case the function do not perform
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 % accuracy test but simply run how far maximum number of iteration is
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 % reached. Model order is fixed by minorder parameter.
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29
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30 plfit1 = plist('FS',10,... % Sampling frequency for the model filters
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31 'AutoSearch','off',... % Automatically search for a good model
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 'StartPolesOpt','c1',... % Define the properties of the starting poles - complex distributed in the unitary circle
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33 'maxiter',30,... % maximum number of iteration per model order
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34 'minorder',19,... % fixed model order
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35 'weightparam','abs',... % assign weights as 1./abs(data)
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36 'Plot','on',... % set the plot on or off
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37 'ForceStability','on',... % force to output a stable ploes model
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38 'CheckProgress','off'); % display fitting progress on the command window
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39
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 % Do the fit
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41 fobj = zDomainFit(rfilt,plfit1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 % setting input and output units for fitted model
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43
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44 %% 3) Compare results
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45
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46 % Extracting residues and poles from fit results
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47 fRes = zeros(numel(fobj),1); % fit residue vector initialization
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48 fPoles = zeros(numel(fobj),1); % fit poles vector initialization
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49
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 % extracting data from fitted filters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 for ii = 1:numel(fobj)
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52 fRes(ii,1) = fobj(ii).a(1);
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53 fPoles(ii,1) = -1*fobj(ii).b(2);
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54 end
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55 [fRes,idx] = sort(fRes);
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56 fPoles = fPoles(idx);
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57
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58 % starting model residues and poles
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 mRes = [2.44554138162509e-011 - 1.79482547894083e-011i;
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60 2.44554138162509e-011 + 1.79482547894083e-011i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 2.66402334803101e-009 + 1.1025122049153e-009i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 2.66402334803101e-009 - 1.1025122049153e-009i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 -7.3560293387644e-009;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 -1.82811618589835e-009 - 1.21803627800855e-009i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 -1.82811618589835e-009 + 1.21803627800855e-009i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 1.16258677367555e-009;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 1.65216557639319e-016;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 -1.78092396888606e-016;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 -2.80420398962379e-017;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 9.21305973049041e-013 - 8.24686706827269e-014i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 9.21305973049041e-013 + 8.24686706827269e-014i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 5.10730060739905e-010 - 3.76571756625722e-011i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 5.10730060739905e-010 + 3.76571756625722e-011i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 3.45893698149735e-009;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 3.98139182134446e-014 - 8.25503935419059e-014i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 3.98139182134446e-014 + 8.25503935419059e-014i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 -1.40595719147164e-011];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 [mRes,idx] = sort(mRes);
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79
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80 mPoles = [0.843464045655194 - 0.0959986292915475i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 0.843464045655194 + 0.0959986292915475i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 0.953187595424927 - 0.0190043625473383i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 0.953187595424927 + 0.0190043625473383i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 0.967176277937188;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 0.995012027005247 - 0.00268322602801729i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 0.995012027005247 + 0.00268322602801729i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 0.996564761885673;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 0.999999366165445;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 0.999981722418555;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 0.999921882627659;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 0.999624431675213 - 0.000813407848742761i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 0.999624431675213 + 0.000813407848742761i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 0.997312006278751 - 0.00265611346834941i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 0.997312006278751 + 0.00265611346834941i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 0.990516544257531;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 0.477796923118318 - 0.311064085401834i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 0.477796923118318 + 0.311064085401834i;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 0];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 mPoles = mPoles(idx);
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100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 % Check the relative difference
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 (mRes-fRes)./abs(mRes)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 (mPoles-fPoles)./abs(mPoles)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 % Results are accurate to the 7th decimal digit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105