Class HomeostaticMaxEnt
source code
object --+
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param.parameterized.Parameterized --+
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base.functionfamily.OutputFn --+
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OutputFnWithState --+
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OutputFnWithRandomState --+
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HomeostaticMaxEnt
Implementation of homeostatic intrinsic plasticity from Jochen Triesch,
ICANN 2005, LNCS 3696 pp.65-70.
A sigmoid activation function is adapted automatically to achieve
desired average firing rate and approximately exponential
distribution of firing rates (for the maximum possible entropy).
Note that this OutputFn has state, so the history of calls to it
will affect future behavior. The plastic parameter can be used
to disable changes to the state.
Also calculates average activity as useful debugging information,
for use with ValueTrackingOutoutFn Average activity is calculated as
an exponential moving average with a smoothing factor (smoothing).
For more information see:
NIST/SEMATECH e-Handbook of Statistical Methods, Single Exponential Smoothing
http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc431.htm
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__init__(self,
**params)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature |
source code
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Inherited from OutputFnWithState:
override_plasticity_state,
restore_plasticity_state
Inherited from base.functionfamily.OutputFn:
__add__
Inherited from param.parameterized.Parameterized:
__getstate__,
__repr__,
__setstate__,
__str__,
debug,
defaults,
force_new_dynamic_value,
get_param_values,
get_value_generator,
inspect_value,
message,
print_param_values,
script_repr,
set_dynamic_time_fn,
verbose,
warning
Inherited from object:
__delattr__,
__getattribute__,
__hash__,
__new__,
__reduce__,
__reduce_ex__,
__setattr__
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Inherited from object:
__class__
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x.__init__(...) initializes x; see x.__class__.__doc__ for signature
- Overrides:
object.__init__
- (inherited documentation)
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eta
Learning rate for homeostatic plasticity.
- Value:
param.Number(default= 0.0002, doc= "Learning rate for homeostatic plasticity.")
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mu
Target average firing rate.
- Value:
param.Number(default= 0.01, doc= "Target average firing rate.")
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smoothing
Weighting of previous activity vs. current activity when calculating the average.
- Value:
param.Number(default= 0.9997, doc= """
Weighting of previous activity vs. current activity when calculating the a
verage.""")
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a_init
Multiplicative parameter controlling the exponential.
- Value:
param.Parameter(default= None, doc= "Multiplicative parameter controlling the expo
nential.")
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b_init
Additive parameter controlling the exponential.
- Value:
param.Parameter(default= None, doc= "Additive parameter controlling the exponentia
l.")
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step
How often to update the a and b parameters.
For instance, step=1 means to update it every time this OF is
called; step=2 means to update it every other time.
- Value:
param.Number(default= 1, doc= """
How often to update the a and b parameters.
For instance, step=1 means to update it every time this OF is
called; step=2 means to update it every other time.""")
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