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PYTHON/JUPYTER NOTEBOOKS  given the attached fourier data : # Measurements of fourier data     data = [         [-2.00, -9.37], [-1.00, 10.00], [-1.14, 10.83], [-0.29, -13.88],         [0.00, -18.00], [0.57, -1.83], [1.00, 14.00], [1.43, 14.5],         [2.00, 0.00], [2.29, -1.38], [3.00, 28.00], [3.14, 35.64],         [4.00, 37.88], [5.00, -23.00], [4.86, -17.52], [5.71, -14.63],         [6.00, -1.00], [6.50, -15.00], [6.57, -1.73], [7.00, 12.00],         [7.43, 5.97], [7.50, 2.00], [8.29, 22.78], [9.00, 1.00],         [9.14, -6.41], [10.0, -9.37] Fit the data with the linear least-squares fit method using Fourier basis functions. Use 10 pairs of sines and cosines and create the plots/results below. Explain the procedure and results. Results : x_vec = [ 4.995 -1.624 9.339 -10.278 -11.465 4.794 7.555 -14.394 1.139 -2.097 0.597 0.421 3.29 6.218 0.639 0.823 -5.083 -2.538 -0.87 -0.107 1.576] Local Relative Error (discarding y values < 0.1): mean [%] = 21.79 std [%] = 94.20 max, min [%] = 390.26, -74.18   discarding |?| values < 0.1

PYTHON/JUPYTER NOTEBOOKS  given the attached fourier data : # Measurements of fourier data     data = [         [-2.00, -9.37], [-1.00, 10.00], [-1.14, 10.83], [-0.29, -13.88],         [0.00, -18.00], [0.57, -1.83], [1.00, 14.00], [1.43, 14.5],         [2.00, 0.00], [2.29, -1.38], [3.00, 28.00], [3.14, 35.64],         [4.00, 37.88], [5.00, -23.00], [4.86, -17.52], [5.71, -14.63],         [6.00, -1.00], [6.50, -15.00], [6.57, -1.73], [7.00, 12.00],         [7.43, 5.97], [7.50, 2.00], [8.29, 22.78], [9.00, 1.00],         [9.14, -6.41], [10.0, -9.37] Fit the data with the linear least-squares fit method using Fourier basis functions. Use 10 pairs of sines and cosines and create the plots/results below. Explain the procedure and results. Results : x_vec = [ 4.995 -1.624 9.339 -10.278 -11.465 4.794 7.555 -14.394 1.139 -2.097 0.597 0.421 3.29 6.218 0.639 0.823 -5.083 -2.538 -0.87 -0.107 1.576] Local Relative Error (discarding y values < 0.1): mean [%] = 21.79 std [%] = 94.20 max, min [%] = 390.26, -74.18   discarding |?| values < 0.1

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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PYTHON/JUPYTER NOTEBOOKS 

given the attached fourier data :

# Measurements of fourier data
    data = [
        [-2.00, -9.37], [-1.00, 10.00], [-1.14, 10.83], [-0.29, -13.88],
        [0.00, -18.00], [0.57, -1.83], [1.00, 14.00], [1.43, 14.5],
        [2.00, 0.00], [2.29, -1.38], [3.00, 28.00], [3.14, 35.64],
        [4.00, 37.88], [5.00, -23.00], [4.86, -17.52], [5.71, -14.63],
        [6.00, -1.00], [6.50, -15.00], [6.57, -1.73], [7.00, 12.00],
        [7.43, 5.97], [7.50, 2.00], [8.29, 22.78], [9.00, 1.00],
        [9.14, -6.41], [10.0, -9.37]

Fit the data with the linear least-squares fit method using Fourier basis functions. Use 10 pairs of sines and cosines and create the plots/results below. Explain the procedure and results.

Results :

x_vec = [ 4.995 -1.624 9.339 -10.278 -11.465 4.794 7.555 -14.394 1.139 -2.097 0.597 0.421 3.29 6.218 0.639 0.823 -5.083 -2.538 -0.87 -0.107 1.576]

Local Relative Error (discarding y values < 0.1): mean [%] = 21.79
std [%] = 94.20
max, min [%] = 390.26, -74.18
 

discarding |?| values < 0.1

Thank You

 

Power [y au] 8 7 6 2 1 0 Power Spectrum N = 10 4 Cycle Frequency (wk = kµ/2π) [cycles/period] 10
Transcribed Image Text:Power [y au] 8 7 6 2 1 0 Power Spectrum N = 10 4 Cycle Frequency (wk = kµ/2π) [cycles/period] 10
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