Gain correction factor for y2 = 0.990300 2024 Al f_r_e_f = 0.6700 MHz JE121AD Model contains constant terms in both waveforms. No. of linear parameters: 2 Model contains 2 coupled sine/cosine waves No. of linear parameters: 6 No. of nonlinear parameters: 4 Reference signal not in the data (No pure exponential in model). No pure sine/cosine waves in model Weights are set to 1 Enter initial values of nonlinear parameters: nonlinear parameters: 1 3.000000E-03 2 -6.700000E-01 3 3.000000E-03 4 -1.200000E-01 Terms with nonlin parm 1: 3 4 0 0 0 0 0 Terms with nonlin parm 2: 3 4 0 0 0 0 0 Terms with nonlin parm 3: 5 6 0 0 0 0 0 Terms with nonlin parm 4: 5 6 0 0 0 0 0 1 iteration 0 nonlinear parameters 7.0599249E+00 3.5275045E+00 2.3548787E+03 -3.5184342E-03 0 weighted norm of residual = 3.1017136E+00 nu = 0.1000000E+01 iteration 1 nonlinear parameters 1.4947568E-02 -6.6926565E-01 1.2746895E-02 -1.1960907E-01 1 weighted norm of residual = 1.8526563E+00 nu = 0.5000000E+00 norm(delta-alf) / norm(alf) = 2.270E-02 iteration 2 nonlinear parameters 2.6089058E-02 -6.6811930E-01 2.1991808E-02 -1.1909752E-01 1 weighted norm of residual = 8.5107261E-01 nu = 0.2500000E+00 norm(delta-alf) / norm(alf) = 2.139E-02 iteration 3 nonlinear parameters 3.0118932E-02 -6.6689999E-01 2.6359177E-02 -1.1865441E-01 1 weighted norm of residual = 5.4695890E-01 nu = 0.1250000E+00 norm(delta-alf) / norm(alf) = 8.964E-03 iteration 4 nonlinear parameters 2.9360770E-02 -6.6663862E-01 2.6856522E-02 -1.1853692E-01 1 weighted norm of residual = 5.3559617E-01 nu = 0.6250000E-01 norm(delta-alf) / norm(alf) = 1.402E-03 1 iteration 5 nonlinear parameters 2.9324742E-02 -6.6664110E-01 2.6858491E-02 -1.1853270E-01 1 weighted norm of residual = 5.3559000E-01 nu = 0.3125000E-01 norm(delta-alf) / norm(alf) = 5.368E-05 iteration 6 nonlinear parameters 2.9324595E-02 -6.6664113E-01 2.6858512E-02 -1.1853267E-01 1 weighted norm of residual = 5.3559000E-01 nu = 0.1562500E-01 norm(delta-alf) / norm(alf) = 2.281E-07 iteration 7 nonlinear parameters 2.9324594E-02 -6.6664113E-01 2.6858513E-02 -1.1853267E-01 1 weighted norm of residual = 5.3559000E-01 nu = 0.7812500E-02 norm(delta-alf) / norm(alf) = 1.513E-09 ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' linear parameters -0.5429698E-03 -0.4121016E-03 0.4566922E+00 0.2890313E+00 -0.2625714E+00 0.2667368E+00 nonlinear parameters 0.2932459E-01 -0.6666411E+00 0.2685851E-01 -0.1185327E+00 weighted norm of residual = 0.5355900E+00 weighted estimated variance = 0.1066382E-03 ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 1 Param. Estimate Std. Deviation t-ratio E( 1) -5.429698E-04 2.812987E-04 -1.930225E+00 F( 1) -4.121016E-04 2.812987E-04 -1.464996E+00 E( 2) 4.566922E-01 4.412160E-03 1.035076E+02 F( 2) 2.890313E-01 4.412160E-03 6.550789E+01 E( 3) -2.625714E-01 3.824786E-03 -6.864995E+01 F( 3) 2.667368E-01 3.824786E-03 6.973900E+01 ------------------------------------------------------- B( 2) 2.932459E-02 1.805321E-04 1.624342E+02 C( 2) -6.666411E-01 2.873258E-05 -2.320158E+04 B( 3) 2.685851E-02 2.166209E-04 1.239886E+02 C( 3) -1.185327E-01 3.447628E-05 -3.438093E+03 wtd residual sum of squares: 2.868566E-01 wtd residual mean square: 1.066382E-04 wtd residual standard error: 1.032658E-02 coefficient of determination (r-square): 9.846646E-01 1 For Damped Sine/Cosine Pairs ---------------------------- A( 2) = 5.4046912E-01 +/- 4.4121595E-03 [V], t = 1.22E+02 B( 2) = 2.9324594E-02 +/- 1.8053211E-04 [ms-1], t = 1.62E+02 C( 2) = -6.6664113E-01 +/- 2.8732577E-05 [kHz], t =-2.32E+04 D( 2) = -1.3470888E-01 +/- -1.9489843E-03 [ms] A( 3) = 3.7428900E-01 +/- 3.8247864E-03 [V], t = 9.79E+01 B( 3) = 2.6858513E-02 +/- 2.1662086E-04 [ms-1], t = 1.24E+02 C( 3) = -1.1853267E-01 +/- 3.4476280E-05 [kHz], t =-3.44E+03 D( 3) = -3.1531185E+00 +/- -1.3720887E-02 [ms] Correlation Matrix E 01 F 01 E 2 F 2 E 3 F 3 B 2 C 2 B 3 C 3 E 01 1.000 0.000 -0.004 0.006 -0.013 -0.037 0.000 -0.006 -0.013 -0.029 F 01 0.000 1.000 -0.006 -0.004 0.037 -0.013 -0.006 0.000 -0.029 0.013 E 2 -0.004 -0.006 1.000 0.000 -0.025 -0.013 0.784 0.496 0.006 -0.021 F 2 0.006 -0.004 0.000 1.000 0.013 -0.025 0.496 -0.784 -0.021 -0.006 E 3 -0.013 0.037 -0.025 0.013 1.000 0.000 -0.010 -0.019 -0.647 0.657 F 3 -0.037 -0.013 -0.013 -0.025 0.000 1.000 -0.019 0.010 0.657 0.647 B 2 0.000 -0.006 0.784 0.496 -0.010 -0.019 1.000 0.000 -0.005 -0.016 C 2 -0.006 0.000 0.496 -0.784 -0.019 0.010 0.000 1.000 0.016 -0.005 B 3 -0.013 -0.029 0.006 -0.021 -0.647 0.657 -0.005 0.016 1.000 0.000 C 3 -0.029 0.013 -0.021 -0.006 0.657 0.647 -0.016 -0.005 0.000 1.000 1 1 FOR Cosine Wave PERIODOGRAM Sum of periodogram ordinates = 8.8678E-01 Average periodogram ordinate = 1.0825E-04 Maximum periodogram ordinate freq. , period , power = 1.546209 0.6467 3.0333E-02 P_maximum / P_average = 2.8022E+02 Fisher statistic = 1.1999E+01 The maximum peak is significantly above the average value Time-series differs significantly from white noise 7223 / 8192 periodogram ordinates outside white noise band 1 1 FOR Sine Wave PERIODOGRAM Sum of periodogram ordinates = 8.5370E-01 Average periodogram ordinate = 1.0421E-04 Maximum periodogram ordinate freq. , period , power = 1.546209 0.6467 2.8405E-02 P_maximum / P_average = 2.7257E+02 Fisher statistic = 1.1999E+01 The maximum peak is significantly above the average value Time-series differs significantly from white noise 7198 / 8192 periodogram ordinates outside white noise band