brainpy.encoding.WeightedPhaseEncoder#

class brainpy.encoding.WeightedPhaseEncoder(min_val, max_val, num_phase, weight_fun=None)[source]#

Encode the rate input into the spike train according to [1].

The main idea of the weighted spikes is assigning different weights to different phases (or to spikes in those phases) in order to pack more information into the spikes. This is the major difference from a conventional rate coding scheme that assigns the same weight to every spike [1].

Parameters:

  • min_val (float) – The minimal value in the given data x, used to the data normalization.

  • max_val (float) – The maximum value in the given data x, used to the data normalization.

  • num_phase (int) – The number of the encoding period.

  • weight_fun (Callable) – The function to generate weight at the phase \(i\).

References

__init__(min_val, max_val, num_phase, weight_fun=None)[source]#

Methods

__init__(min_val, max_val, num_phase[, ...])

cpu()

Move all variable into the CPU device.

cuda()

Move all variables into the GPU device.

load_state_dict(state_dict[, warn, compatible])

Copy parameters and buffers from state_dict into this module and its descendants.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

register_implicit_nodes(*nodes[, node_cls])

register_implicit_vars(*variables[, var_cls])

save_states(filename[, variables])

Save the model states.

state_dict()

Returns a dictionary containing a whole state of the module.

to(device)

Moves all variables into the given device.

tpu()

Move all variables into the TPU device.

train_vars([method, level, include_self])

The shortcut for retrieving all trainable variables.

tree_flatten()

Flattens the object as a PyTree.

tree_unflatten(aux, dynamic_values)

Unflatten the data to construct an object of this class.

unique_name([name, type_])

Get the unique name for this object.

vars([method, level, include_self, ...])

Collect all variables in this node and the children nodes.

Attributes

name

Name of the model.