nengolib.Connection¶
-
class
nengolib.Connection(pre, post, solver=LstsqL2(reg=0.1, solver=Cholesky(transpose=None), weights=False), **kwargs)[source]¶ Drop-in replacement for
nengo.Connection.Extends
nengo.Connectionto improve decoding by using a bias. If thepreobject is anengo.Ensemble, then a bias will be included in its decoders. This automatically improves the decoding of functions with a constant offset when the ensemble has few neurons. This is equivalent to a change in postsynaptic biases (in effect changing the representation to be centered around some constant offset, that is discovered optimally).Parameters: - pre :
nengo.Ensembleornengo.ensemble.Neuronsornengo.Node Nengo source object for the connection.
- post :
nengo.Ensembleornengo.ensemble.Neuronsornengo.Nodeornengo.Probe Nengo destination object for the connection.
- solver :
nengo.solvers.Solver, optional Solver to use for decoded bias and connection. Defaults to
nengo.solvers.LstsqL2.- **kwargs :
dictionary, optional Additional keyword arguments passed to
nengo.Connection.
See also
Attributes: - eval_points
- function
- function_info
Connection-specific validation for functions.
- is_decoded
- label
A parameter where the value is a string.
learning_rule(LearningRule or iterable) Connectable learning rule object(s).
- learning_rule_type
Connection-specific validation for learning rules.
- modulatory
A parameter that is no longer supported.
paramsReturns a list of parameter names that can be set.
- post
- post_obj
- post_slice
- pre
- pre_obj
- pre_slice
- scale_eval_points
A parameter where the value is a boolean.
- seed
A parameter where the value is an integer.
size_in(int) The number of output dimensions of the pre object.
size_mid(int) The number of output dimensions of the function, if specified.
size_out(int) The number of input dimensions of the post object.
- solver
Connection-specific validation for decoder solvers.
- synapse
- transform
The transform additionally validates size_out.
Methods
copy - pre :