.. note::
    :class: sphx-glr-download-link-note

    Click :ref:`here <sphx_glr_download_auto_examples_plot_2_6_monocomp_nonstat_colored_gaussian_noise.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_2_6_monocomp_nonstat_colored_gaussian_noise.py:


=========================
Noisy Monocomponent Chirp
=========================

This example demonstrates the construction of a monocomponent signal with
linear frequency modulation and colored Gaussian noise.

Figure 2.9 from the tutorial.



.. image:: /auto_examples/images/sphx_glr_plot_2_6_monocomp_nonstat_colored_gaussian_noise_001.png
    :class: sphx-glr-single-img





.. code-block:: default


    from tftb.generators import fmlin, amgauss, noisecg, sigmerge
    from numpy import real
    import matplotlib.pyplot as plt

    fm, _ = fmlin(256)
    am = amgauss(256)
    signal = fm * am

    noise = noisecg(256, .8)
    sign = sigmerge(signal, noise, -10)

    plt.plot(real(sign))
    plt.xlabel('Time')
    plt.ylabel('Real part')
    plt.title('Gaussian transient signal embedded in -10 dB colored Gaussian noise')
    plt.xlim(0, 256)
    plt.grid()
    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.193 seconds)


.. _sphx_glr_download_auto_examples_plot_2_6_monocomp_nonstat_colored_gaussian_noise.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_2_6_monocomp_nonstat_colored_gaussian_noise.py <plot_2_6_monocomp_nonstat_colored_gaussian_noise.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_2_6_monocomp_nonstat_colored_gaussian_noise.ipynb <plot_2_6_monocomp_nonstat_colored_gaussian_noise.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_