Examples

Introductory tutorials

These are tutorial-style examples that focus on introducing the basic principles of Nengo.

Representing values

• A single neuron
• Two neurons
• Many neurons
• 2-dimensional representation
• Combining
• Addition

Computing functions

• Communication channel
• Squaring the input
• Multiplication

Building dynamical systems

• Integrator
• Controlled integrator
• Controlled integrator 2
• A simple harmonic oscillator
• Controlled oscillator
• The Lorenz chaotic attractor

Advanced examples

These examples illustrate some of the more advanced uses of Nengo.

Nodes

• Delaying a connection with a node

Processes

• Processes and how to use them

Ensembles

• Tuning curves
• Using the Izhikevich neuron model

Connections

• Inhibitory gating of ensembles
• Improving function approximation by adjusting tuning curves

Learning

• Learning a communication channel
• Learning to square the input
• Learning to compute a product
• Unsupervised learning
• Learning new associations
• Legendre Memory Units in Nengo

Networks

• Ensemble array
• Matrix multiplication
• The basal ganglia
• Integrator

Under the hood

• Adding new objects to Nengo
• NEF summary
• The NEF algorithm