def __init__(self, size, dt=0.001, t_rc=0.02, t_ref=0.002):
Neuron.__init__(self, size, dt)
self.t_rc = t_rc
self.t_ref = t_ref
self.voltage = theano.shared(
numpy.zeros(size).astype('float32')) # internal variables
self.refractory_time = theano.shared(
numpy.zeros(size).astype('float32')) # internal variables
def __init__(self, inputs, weights, bias):
Neuron.__init__(self, inputs)
# NOTE: The weights and bias properties here are not
# numbers, but rather references to other neurons.
# The weight and bias values are stored within the
# respective neurons.
self.weights = weights
self.bias = bias
def __init__(self, size, dt=0.001, tau_rc=0.02, tau_ref=0.002):
"""Constructor for a set of LIF rate neuron
:param int size: number of neurons in set
:param float dt: timestep for neuron update function
:param float t_rc: the RC time constant
:param float tau_ref: refractory period length (s)
"""
Neuron.__init__(self, size, dt)
self.tau_rc = tau_rc
self.tau_ref = tau_ref
def __init__(self, size, dt=0.001, tau_rc=0.02, tau_ref=0.002):
"""Constructor for a set of LIF rate neuron
:param int size: number of neurons in set
:param float dt: timestep for neuron update function
:param float t_rc: the RC time constant
:param float tau_ref: refractory period length (s)
"""
Neuron.__init__(self, size, dt)
self.tau_rc = tau_rc
self.tau_ref = tau_ref
def __init__(self, size, dt=0.001, tau_rc=0.02, tau_ref=0.002):
""" Constructor for a set of LIF rate neuron
:param int size: number of neurons in set
:param float dt: timestep for neuron update function
:param float tau_rc: the RC time constant
:param float tau_ref: refractory period length (s)
"""
Neuron.__init__(self, size, dt)
self.tau_rc = tau_rc
self.tau_ref = tau_ref
self.voltage = theano.shared(numpy.zeros(size).astype('float32')) # internal variables
self.refractory_time = theano.shared(numpy.zeros(size).astype('float32')) # internal variables
def __init__(self, size, dt=0.001, tau_rc=0.02, tau_ref=0.002):
""" Constructor for a set of LIF rate neuron
:param int size: number of neurons in set
:param float dt: timestep for neuron update function
:param float tau_rc: the RC time constant
:param float tau_ref: refractory period length (s)
"""
Neuron.__init__(self, size, dt)
self.tau_rc = tau_rc
self.tau_ref = tau_ref
self.voltage = theano.shared(
numpy.zeros(size).astype('float32')) # internal variables
self.refractory_time = theano.shared(
numpy.zeros(size).astype('float32')) # internal variables
def __init__(self, pos, value=False):
super().__init__()
self.setPos(pos)
Neuron.__init__(self, NEURONTYPEIN)
self.value = value
def __init__(self,size,dt=0.001,t_rc=0.02,t_ref=0.002):
Neuron.__init__(self,size,dt)
self.t_rc=t_rc
self.t_ref=t_ref
self.voltage=theano.shared(numpy.zeros(size).astype('float32')) # internal variables
self.refractory_time=theano.shared(numpy.zeros(size).astype('float32')) # internal variables
def __init__(self, *inputs):
Neuron.__init__(self, inputs)
def __init__(self):
# An Input neuron has no inbound neurons,
# so no need to pass anything to the Neuron instantiator.
Neuron.__init__(self)
def __init__(self,size,dt=0.001,t_rc=0.02,t_ref=0.002):
Neuron.__init__(self,size,dt)
self.t_rc=t_rc
self.t_ref=t_ref
def __init__(self, size, dt=0.001, t_rc=0.02, t_ref=0.002):
Neuron.__init__(self, size, dt)
self.t_rc = t_rc
self.t_ref = t_ref
def __init__(self, alpha=0.01, epochs=10, seed=2): Neuron.__init__(self, alpha, epochs, seed)