Note
This documentation is for a development version. Click here for the latest stable release (v0.5.0).
Learning rules¶
These learning rule types can be used in any place that Nengo learning rule types can be used.

class
nengo_extras.learning_rules.
AML
(d, learning_rate=1.0)[source]¶ Association matrix learning rule (AML).
Enables oneshot learning without catastrophic forgetting of outer product association matrices.
The cue is provided by the presynaptic ensemble. The error signal is split up:
error[0]
provides a scaling factor to the learning rate.error[1]
provides a decay rate (i.e., weights are multiplied with this value in every time step),error[2:]
provides the target vector.The update is given by:
decoders[...] *= error[1] # decay decoders[...] += alpha * error[0] * error[2:, None] * np.dot( pre, base_decoders.T)
where alpha is the learning rate adjusted for dt and base_decoders is the decoder matrix for decoding the identity from the preensemble.
 Parameters
 dint
Dimensionality of input and output vectors (error signal will be d+2).
 learning_ratefloat, optional
Learning rate (increase of dot product similarity per second).

class
nengo_extras.learning_rules.
DeltaRule
(learning_rate=0.0001, pre_tau=0.005, post_fn=None, post_tau=None, post_target='in')[source]¶ Implementation of the Delta rule.
By default, this implementation pretends the neurons are linear, and thus does not require the derivative of the postsynaptic neuron activation function. The derivative function, or a surrogate function, for the postsynaptic neurons can be provided in
post_fn
.The update is given by:
delta W_ij = eta a_j e_i f(u_i)
where
e_i
is the input error in the postsynaptic neuron space,a_j
is the output activity for presynaptic neuron j,u_i
is the input for postsynaptic neuron i, andf
is a provided function. Parameters
 learning_ratefloat
A scalar indicating the rate at which weights will be adjusted.
 pre_taufloat
Filter constant on the presynaptic output
a_j
. post_fncallable
Function
f
to apply to the postsynaptic inputsu_i
. The default ofNone
means thef(u_i)
term is omitted. post_taufloat
Filter constant on the postsynaptic input
u_i
. This defaults toNone
because these should typically be filtered by the connection.