:orphan:
.. _general_examples:
Examples Gallery
================
.. contents:: Contents
:local:
:depth: 3
.. raw:: html
.. raw:: html
.. only:: html
.. image:: /auto_examples/images/thumb/sphx_glr_plot_custom_density_thumb.png
:alt: Using a custom density with Picard
:ref:`sphx_glr_auto_examples_plot_custom_density.py`
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Using a custom density with Picard
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.. only:: html
.. image:: /auto_examples/images/thumb/sphx_glr_plot_ica_synth_thumb.png
:alt: Blind source separation using Picard and Picard-O
:ref:`sphx_glr_auto_examples_plot_ica_synth.py`
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Blind source separation using Picard and Picard-O
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.. only:: html
.. image:: /auto_examples/images/thumb/sphx_glr_plot_ica_eeg_thumb.png
:alt: Blind source separation using preconditioned ICA on EEG
:ref:`sphx_glr_auto_examples_plot_ica_eeg.py`
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Blind source separation using preconditioned ICA on EEG
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.. only:: html
.. image:: /auto_examples/images/thumb/sphx_glr_plot_ecg_detection_thumb.png
:alt: Comparing Picard and FastICA for the task of detecting ECG artifacts in MEG
:ref:`sphx_glr_auto_examples_plot_ecg_detection.py`
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Comparing Picard and FastICA for the task of detecting ECG artifacts in MEG
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.. only:: html
.. image:: /auto_examples/images/thumb/sphx_glr_plot_faces_decomposition_thumb.png
:alt: Comparison of Picard-O and FastICA on faces data
:ref:`sphx_glr_auto_examples_plot_faces_decomposition.py`
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Comparison of Picard-O and FastICA on faces data
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.. toctree::
:hidden:
/auto_examples/plot_custom_density
/auto_examples/plot_ica_synth
/auto_examples/plot_ica_eeg
/auto_examples/plot_ecg_detection
/auto_examples/plot_faces_decomposition
.. only:: html
.. container:: sphx-glr-footer sphx-glr-footer-gallery
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download all examples in Python source code: auto_examples_python.zip `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download all examples in Jupyter notebooks: auto_examples_jupyter.zip `
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery