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GNCN-t1-SC (Olshausen & Field, 1996)

This circuit implements the sparse coding model proposed in (Olshausen & Field, 1996) [1]. Specifically, this model is unsupervised and can be used to process sensory pattern (row) vector(s) x to infer internal latent states. This class offers, beyond settling and update routines, a projection function by which ancestral sampling may be carried out given the underlying directed generative model formed by this NGC system.

The GNCN-t1-SC is graphically depicted by the following graph:

.. table::
   :align: center

   +--------------------------------------------------+
   | .. image:: ../images/museum/gncn_t1_sc.png       |
   |   :scale: 75%                                    |
   |   :align: center                                 |
   +--------------------------------------------------+

.. autoclass:: ngclearn.museum.gncn_t1_sc.GNCN_t1_SC
  :noindex:

  .. automethod:: project
    :noindex:
  .. automethod:: settle
    :noindex:
  .. automethod:: calc_updates
    :noindex:
  .. automethod:: clear
    :noindex:

References:
[1] Olshausen, B., Field, D. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381, 607–609 (1996).