Sascha Spors, Professorship Signal Theory and Digital Signal Processing, Institute of Communications Engineering (INT), Faculty of Computer Science and Electrical Engineering (IEF), University of Rostock, Germany
Summer Semester 2022 (Bachelor Course #24015)
Feel free to contact lecturer frank.schultz@uni-rostock.de
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import sici
N = 7
x = np.linspace(0, N*2*np.pi, 2**10)
si, _ = sici(x)
plt.figure(figsize=(6, 4))
plt.plot(x, si, lw=2)
plt.xticks(np.arange(0, N+1)*2*np.pi, ['0', r'$2\pi$', r'$4\pi$',
r'$6\pi$', r'$8\pi$', r'$10\pi$', r'$12\pi$', r'$14\pi$'])
plt.yticks(np.arange(0, 4)*np.pi/4, ['0', r'$\pi/4$', r'$\pi/2$', r'$3\pi/4$'])
plt.xlim(0, 14*np.pi)
plt.ylim(0, 3/4*np.pi)
plt.xlabel(r'$\omega$')
plt.ylabel(
r'$\mathrm{Si}(\omega) = \int_0^\omega\,\,\,\frac{\sin \nu}{\nu}\,\,\,\mathrm{d}\nu$')
#plt.title('Sine Integral Si(x)')
plt.grid(True)
plt.savefig('sine_intergral_0A13DD5E57.pdf')
This tutorial is provided as Open Educational Resource (OER), to be found at
https://github.com/spatialaudio/signals-and-systems-exercises
accompanying the OER lecture
https://github.com/spatialaudio/signals-and-systems-lecture.
Both are licensed under a) the Creative Commons Attribution 4.0 International
License for text and graphics and b) the MIT License for source code.
Please attribute material from the tutorial as Frank Schultz,
Continuous- and Discrete-Time Signals and Systems - A Tutorial Featuring
Computational Examples, University of Rostock with
github URL, commit number and/or version tag, year, (file name and/or content)
.