Model of oscillatory network that is based on the Eckhorn model. More...
Public Member Functions | |
def | __init__ (self, num_osc, parameters=None, type_conn=conn_type.ALL_TO_ALL, type_conn_represent=conn_represent.MATRIX, height=None, width=None, ccore=True) |
Constructor of oscillatory network is based on Kuramoto model. More... | |
def | __del__ (self) |
Default destructor of PCNN. | |
def | __len__ (self) |
(uint) Returns size of oscillatory network. | |
def | simulate (self, steps, stimulus) |
Performs static simulation of pulse coupled neural network using. More... | |
Public Member Functions inherited from pyclustering.nnet.network | |
def | height (self) |
Height of the network grid (that is defined by amout of oscillators in each column), this value is zero in case of non-grid structure. More... | |
def | width (self) |
Width of the network grid, this value is zero in case of non-grid structure. More... | |
def | structure (self) |
Type of network structure that is used for connecting oscillators. | |
def | __init__ (self, num_osc, type_conn=conn_type.ALL_TO_ALL, conn_repr=conn_represent.MATRIX, height=None, width=None) |
Constructor of the network. More... | |
def | __len__ (self) |
Returns size of the network that is defined by amount of oscillators. | |
def | has_connection (self, i, j) |
Returns True if there is connection between i and j oscillators and False - if connection doesn't exist. More... | |
def | set_connection (self, i, j) |
Couples two specified oscillators in the network with dynamic connections. More... | |
def | get_neighbors (self, index) |
Finds neighbors of the oscillator with specified index. More... | |
Model of oscillatory network that is based on the Eckhorn model.
CCORE option can be used to use the pyclustering core - C/C++ shared library for processing that significantly increases performance.
Here is an example how to perform PCNN simulation:
def pyclustering.nnet.pcnn.pcnn_network.__init__ | ( | self, | |
num_osc, | |||
parameters = None , |
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type_conn = conn_type.ALL_TO_ALL , |
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type_conn_represent = conn_represent.MATRIX , |
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height = None , |
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width = None , |
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ccore = True |
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) |
Constructor of oscillatory network is based on Kuramoto model.
[in] | num_osc | (uint): Number of oscillators in the network. |
[in] | parameters | (pcnn_parameters): Parameters of the network. |
[in] | type_conn | (conn_type): Type of connection between oscillators in the network (all-to-all, grid, bidirectional list, etc.). |
[in] | type_conn_represent | (conn_represent): Internal representation of connection in the network: matrix or list. |
[in] | height | (uint): Number of oscillators in column of the network, this argument is used only for network with grid structure (GRID_FOUR, GRID_EIGHT), for other types this argument is ignored. |
[in] | width | (uint): Number of oscillotors in row of the network, this argument is used only for network with grid structure (GRID_FOUR, GRID_EIGHT), for other types this argument is ignored. |
[in] | ccore | (bool): If True then all interaction with object will be performed via CCORE library (C++ implementation of pyclustering). |
def pyclustering.nnet.pcnn.pcnn_network.simulate | ( | self, | |
steps, | |||
stimulus | |||
) |
Performs static simulation of pulse coupled neural network using.
[in] | steps | (uint): Number steps of simulations during simulation. |
[in] | stimulus | (list): Stimulus for oscillators, number of stimulus should be equal to number of oscillators. |