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GNCN-t1 (Rao & Ballard, 1999)

This circuit implements the model proposed in (Rao & Ballard, 1999) [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 is graphically depicted by the following graph:

.. table::
   :align: center

   +-----------------------------------------------+
   | .. image:: ../images/museum/gncn_t1.png       |
   |   :scale: 75%                                 |
   |   :align: center                              |
   +-----------------------------------------------+

.. autoclass:: ngclearn.museum.gncn_t1.GNCN_t1
  :noindex:

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

References:
[1] Rao, Rajesh PN, and Dana H. Ballard. "Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects." Nature neuroscience 2.1 (1999): 79-87.