Demos

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Crystal Clear app display.png Using emergent

There are a number of demo projects included with the software, which are typically installed in /usr/local/share/Emergent/demo (Linux, Mac) and live in the Emergent\demo application directory under Windows.

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Main User Docs

These can be useful for providing working examples of various types of models and procedures. Each contains its own more detailed documentation that should auto-open when you open the project, so this is just a brief listing of what is available.

See PublishedProjectList for a list of all demos and other projects that have been uploaded to this wiki, and can be directly downloaded here.

demo/programs (Programs)

demo/data_proc (DataProcessing)

demo/leabra (Leabra)

demo/network_misc

This has misc projects for exploring various general neural network functionality:

demo/actr (ACT-R)

  • See ACT-R page for more info about these demos, which are largely taken from the official ACT-R demos that go along with the original lisp version.

demo/bp (Backpropagation)

  • demos/bp_xor -- classic XOR problem -- also includes separate testing and training programs, and a grid view display of the network's performance.
  • demos/bp_softmax -- demonstrates use of SoftMax output layer activation -- now much easier and fully self-contained in version 8.0

demo/cs (Constraint Satisfaction)

  • demos/cs_424 -- classic 4-2-4 auto-encoder using stochastic units, learning via the Boltzmann machine learning rule
  • demos/cs_424 -- deterministic version of the above, learning using CHL (deterministic Boltzmann machine learning rule)
  • demos/cs_ra -- random associator (deterministic) -- learns to associate random bit patterns and is a good test of general learning abilities.

demo/so Self Organizing

  • demos/som -- self-organizing map model -- learns topographic representations of input data in a self-organizing manner
  • demos/cl_lines -- competitive learning self-organizing model, applied to horizontal and vertical lines inputs

demo/virt_env Virtual Environment

  • demos/ve_arm -- A simple simulated robot that can move a 2 jointed arm to reach a target, all under control of the network.
  • demos/cereb_arm -- Model of how the cerebellum learns to control a biophysically-realistic arm with 12 muscles, based on internally-generated error signals.
  • demos/vis_test -- Allows testing of V1 visual filters on well-controlled visual stimuli rendered using a canvas and in a 3D world.
  • demos/vis_test_shadow -- Visual test on 3D world with shadows enabled
  • demos/vis_color_test -- Test of color processing using opponent-coding color channels in the DoG (difference of Gaussian) filter system
  • demos/vis_motion_test -- Test of visual motion filters using stimuli that move in reliable ways (also demonstrates drawing of SVG images on a taCanvas)

demo/audioproc AuditoryProc

  • demos/sound_object -- Test of loading and processing sound files using filters based on the auditory pathways of the brain
  • demos/vocal_tract -- Generates sound output based on a simulation of the human vocal tract configuration, and can produce reasonable speech sounds

Computational Explorations in Cognitive Neuroscience Projects


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