Gain correction factor for y2 = 0.990080 2024 Al f_r_e_f = 0.5758 MHz JE121AA 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 2.900000E-02 2 -1.020000E-02 3 2.900000E-02 4 4.100000E-02 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 -6.5589060E+01 -5.4463926E+00 -2.6164635E+02 6.6343077E+00 0 weighted norm of residual = 3.5427158E-01 nu = 0.1000000E+01 iteration 1 nonlinear parameters 2.9157023E-02 -1.0192452E-02 2.9149057E-02 4.0944818E-02 1 weighted norm of residual = 3.5120387E-01 nu = 0.5000000E+00 norm(delta-alf) / norm(alf) = 3.789E-03 iteration 2 nonlinear parameters 2.9355914E-02 -1.0181066E-02 2.9271519E-02 4.0897025E-02 1 weighted norm of residual = 3.5005206E-01 nu = 0.2500000E+00 norm(delta-alf) / norm(alf) = 4.037E-03 iteration 3 nonlinear parameters 2.9425003E-02 -1.0176675E-02 2.9302895E-02 4.0884046E-02 1 weighted norm of residual = 3.4998781E-01 nu = 0.1250000E+00 norm(delta-alf) / norm(alf) = 1.303E-03 1 iteration 4 nonlinear parameters 2.9430471E-02 -1.0176237E-02 2.9305489E-02 4.0883034E-02 1 weighted norm of residual = 3.4998744E-01 nu = 0.6250000E-01 norm(delta-alf) / norm(alf) = 1.040E-04 iteration 5 nonlinear parameters 2.9430542E-02 -1.0176223E-02 2.9305576E-02 4.0883008E-02 1 weighted norm of residual = 3.4998744E-01 nu = 0.3125000E-01 norm(delta-alf) / norm(alf) = 1.954E-06 iteration 6 nonlinear parameters 2.9430542E-02 -1.0176223E-02 2.9305577E-02 4.0883007E-02 1 weighted norm of residual = 3.4998744E-01 nu = 0.1562500E-01 norm(delta-alf) / norm(alf) = 2.410E-08 ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' linear parameters 0.1344650E-02 -0.9444148E-03 0.3222650E+00 0.2364396E+00 0.5975914E+00 -0.2960627E+00 nonlinear parameters 0.2943054E-01 -0.1017622E-01 0.2930558E-01 0.4088301E-01 weighted norm of residual = 0.3499874E+00 weighted estimated variance = 0.4553577E-04 ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' 1 Param. Estimate Std. Deviation t-ratio E( 1) 1.344650E-03 2.014336E-04 6.675398E+00 F( 1) -9.444148E-04 2.014336E-04 -4.688467E+00 E( 2) 3.222650E-01 3.252236E-03 9.909029E+01 F( 2) 2.364396E-01 3.252236E-03 7.270065E+01 E( 3) 5.975914E-01 3.060721E-03 1.952453E+02 F( 3) -2.960627E-01 3.060721E-03 -9.672974E+01 ------------------------------------------------------- B( 2) 2.943054E-02 1.727140E-04 1.704005E+02 C( 2) -1.017622E-02 2.748828E-05 -3.702022E+02 B( 3) 2.930558E-02 9.898957E-05 2.960471E+02 C( 3) 4.088301E-02 1.575468E-05 2.594975E+03 wtd residual sum of squares: 1.224912E-01 wtd residual mean square: 4.553577E-05 wtd residual standard error: 6.748019E-03 coefficient of determination (r-square): 9.944738E-01 1 For Damped Sine/Cosine Pairs ---------------------------- A( 2) = 3.9969790E-01 +/- 3.2522357E-03 [V], t = 1.23E+02 B( 2) = 2.9430542E-02 +/- 1.7271397E-04 [ms-1], t = 1.70E+02 C( 2) = -1.0176223E-02 +/- 2.7488282E-05 [kHz], t =-3.70E+02 D( 2) = -9.8996522E+00 +/- -1.2725758E-01 [ms] A( 3) = 6.6690975E-01 +/- 3.0607210E-03 [V], t = 2.18E+02 B( 3) = 2.9305577E-02 +/- 9.8989571E-05 [ms-1], t = 2.96E+02 C( 3) = 4.0883007E-02 +/- 1.5754680E-05 [kHz], t = 2.59E+03 D( 3) = -1.7906817E+00 +/- 1.7866273E-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 0.198 -0.268 0.098 0.035 -0.070 0.263 0.053 -0.058 F 01 0.000 1.000 0.268 0.198 -0.035 0.098 0.263 0.070 -0.058 -0.053 E 2 0.198 0.268 1.000 0.000 0.279 0.112 0.736 0.574 0.147 -0.182 F 2 -0.268 0.198 0.000 1.000 -0.112 0.279 0.574 -0.736 -0.182 -0.147 E 3 0.098 -0.035 0.279 -0.112 1.000 0.000 0.110 0.207 0.833 -0.418 F 3 0.035 0.098 0.112 0.279 0.000 1.000 0.207 -0.110 -0.418 -0.833 B 2 -0.070 0.263 0.736 0.574 0.110 0.207 1.000 0.000 -0.004 -0.182 C 2 0.263 0.070 0.574 -0.736 0.207 -0.110 0.000 1.000 0.182 -0.004 B 3 0.053 -0.058 0.147 -0.182 0.833 -0.418 -0.004 0.182 1.000 0.000 C 3 -0.058 -0.053 -0.182 -0.147 -0.418 -0.833 -0.182 -0.004 0.000 1.000 1 1 FOR Cosine Wave PERIODOGRAM Sum of periodogram ordinates = 3.6873E-01 Average periodogram ordinate = 4.5011E-05 Maximum periodogram ordinate freq. , period , power = 4.816872 0.2076 1.1901E-02 P_maximum / P_average = 2.6440E+02 Fisher statistic = 1.1999E+01 The maximum peak is significantly above the average value Time-series differs significantly from white noise 6444 / 8192 periodogram ordinates outside white noise band 1 1 FOR Sine Wave PERIODOGRAM Sum of periodogram ordinates = 3.7453E-01 Average periodogram ordinate = 4.5719E-05 Maximum periodogram ordinate freq. , period , power = 4.816872 0.2076 1.2384E-02 P_maximum / P_average = 2.7086E+02 Fisher statistic = 1.1999E+01 The maximum peak is significantly above the average value Time-series differs significantly from white noise 6444 / 8192 periodogram ordinates outside white noise band