Gain correction factor for y2 = 0.990300 2024 Al f_r_e_f = 0.6697 MHz JE121AC 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-02 2 -4.700000E-01 3 3.000000E-02 4 1.800000E-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 1.1893597E+00 2.1219609E-01 2.5387797E+02 -1.1897537E-04 0 weighted norm of residual = 4.1345469E+00 nu = 0.1000000E+01 iteration 1 nonlinear parameters 6.0489792E-02 -4.6956594E-01 2.9346445E-02 1.8114808E-01 1 weighted norm of residual = 4.1052653E+00 nu = 0.5000000E+00 norm(delta-alf) / norm(alf) = 6.011E-02 iteration 2 nonlinear parameters 1.5458850E-01 -4.6670253E-01 2.7104883E-02 1.8197330E-01 1 weighted norm of residual = 4.0501314E+00 nu = 0.2500000E+00 norm(delta-alf) / norm(alf) = 1.794E-01 iteration 3 nonlinear parameters 4.0571094E-01 -4.4539927E-01 2.5591105E-02 1.8199536E-01 1 weighted norm of residual = 3.9115288E+00 nu = 0.1250000E+00 norm(delta-alf) / norm(alf) = 4.001E-01 .......................................................................... 1 iteration 18 nonlinear parameters 2.9233886E-02 -3.6638237E-01 2.6877357E-02 1.8170453E-01 1 weighted norm of residual = 4.7498724E-01 nu = 0.1668549E-01 norm(delta-alf) / norm(alf) = 1.302E-04 iteration 19 nonlinear parameters 2.9234000E-02 -3.6638238E-01 2.6877362E-02 1.8170454E-01 1 weighted norm of residual = 4.7498724E-01 nu = 0.8342743E-02 norm(delta-alf) / norm(alf) = 2.784E-07 ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' linear parameters -0.3098482E-03 -0.4609359E-03 0.5242583E+00 0.3869658E+00 -0.2006563E+00 0.1073907E+00 nonlinear parameters 0.2923400E-01 -0.3663824E+00 0.2687736E-01 0.1817045E+00 weighted norm of residual = 0.4749872E+00 weighted estimated variance = 0.8387096E-04 ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 1 Param. Estimate Std. Deviation t-ratio E( 1) -3.098482E-04 2.493384E-04 -1.242682E+00 F( 1) -4.609359E-04 2.493384E-04 -1.848636E+00 E( 2) 5.242583E-01 3.892663E-03 1.346786E+02 F( 2) 3.869658E-01 3.892663E-03 9.940901E+01 E( 3) -2.006563E-01 3.393865E-03 -5.912325E+01 F( 3) 1.073907E-01 3.393865E-03 3.164259E+01 ------------------------------------------------------- B( 2) 2.923400E-02 1.319153E-04 2.216119E+02 C( 2) -3.663824E-01 2.099497E-05 -1.745096E+04 B( 3) 2.687736E-02 3.162778E-04 8.498024E+01 C( 3) 1.817045E-01 5.033717E-05 3.609749E+03 wtd residual sum of squares: 2.256129E-01 wtd residual mean square: 8.387096E-05 wtd residual standard error: 9.158109E-03 coefficient of determination (r-square): 9.885083E-01 1 For Damped Sine/Cosine Pairs ---------------------------- A( 2) = 6.5160517E-01 +/- 3.8926630E-03 [V], t = 1.67E+02 B( 2) = 2.9234000E-02 +/- 1.3191528E-04 [ms-1], t = 2.22E+02 C( 2) = -3.6638238E-01 +/- 2.0994969E-05 [kHz], t =-1.75E+04 D( 2) = -2.7621259E-01 +/- -2.5950626E-03 [ms] A( 3) = 2.2758675E-01 +/- 3.3938654E-03 [V], t = 6.71E+01 B( 3) = 2.6877362E-02 +/- 3.1627777E-04 [ms-1], t = 8.50E+01 C( 3) = 1.8170454E-01 +/- 5.0337171E-05 [kHz], t = 3.61E+03 D( 3) = 2.3212966E+00 +/- 1.3061769E-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 0.009 -0.006 -0.003 -0.020 0.002 0.008 -0.006 -0.014 F 01 0.000 1.000 0.006 0.009 0.020 -0.003 0.008 -0.002 -0.014 0.006 E 2 0.009 0.006 1.000 0.000 -0.024 -0.014 0.746 0.551 0.011 -0.018 F 2 -0.006 0.009 0.000 1.000 0.014 -0.024 0.551 -0.746 -0.018 -0.011 E 3 -0.003 0.020 -0.024 0.014 1.000 0.000 -0.009 -0.020 -0.813 0.435 F 3 -0.020 -0.003 -0.014 -0.024 0.000 1.000 -0.020 0.009 0.435 0.813 B 2 0.002 0.008 0.746 0.551 -0.009 -0.020 1.000 0.000 -0.001 -0.016 C 2 0.008 -0.002 0.551 -0.746 -0.020 0.009 0.000 1.000 0.016 -0.001 B 3 -0.006 -0.014 0.011 -0.018 -0.813 0.435 -0.001 0.016 1.000 0.000 C 3 -0.014 0.006 -0.018 -0.011 0.435 0.813 -0.016 -0.001 0.000 1.000 1 1 FOR Cosine Wave PERIODOGRAM Sum of periodogram ordinates = 6.7672E-01 Average periodogram ordinate = 8.2608E-05 Maximum periodogram ordinate freq. , period , power = 2.277500 0.4391 1.4012E-02 P_maximum / P_average = 1.6962E+02 Fisher statistic = 1.1999E+01 The maximum peak is significantly above the average value Time-series differs significantly from white noise 5936 / 8192 periodogram ordinates outside white noise band 1 1 FOR Sine Wave PERIODOGRAM Sum of periodogram ordinates = 6.9217E-01 Average periodogram ordinate = 8.4493E-05 Maximum periodogram ordinate freq. , period , power = 2.277500 0.4391 1.5689E-02 P_maximum / P_average = 1.8568E+02 Fisher statistic = 1.1999E+01 The maximum peak is significantly above the average value Time-series differs significantly from white noise 6085 / 8192 periodogram ordinates outside white noise band