******** Examples ******** Nengo creates these models using the principles of the `Neural Engineering Framework `_. The first set of examples explains these three principles: *representation*, *transformation*, and *dynamics*. For a summary of these principles, see the following example: .. toctree:: examples/nef_summary The following examples give a more detailed presentation: .. toctree:: :maxdepth: 2 representation transformation dynamics Putting these three principles together allows us to scale these examples up to larger networks that do more complex functions. Below are some of these complex functions, as well as other examples that we hope will be helpful as reference when building your own Nengo models. Nodes ===== .. toctree:: examples/delay_node Ensembles ========= .. toctree:: examples/tuning_curves examples/izhikevich Connections =========== .. toctree:: examples/inhibitory_gating Learning ======== .. toctree:: examples/learn_communication_channel examples/learn_square examples/learn_product examples/learn_unsupervised examples/learn_associations Networks ======== .. toctree:: examples/ensemble_array examples/matrix_multiplication examples/basal_ganglia examples/integrator_network Semantic Pointer Architecture ============================= .. toctree:: examples/convolution examples/question examples/question_control examples/question_memory examples/spa_sequence examples/spa_sequence_routed examples/spa_parser Extending Nengo =============== .. toctree:: examples/rectified_linear