Home > TNNT_1_07 > @theta_neuron_network > get_input_neurons.m

get_input_neurons

PURPOSE ^

GET_INPUT_NEURONS returns array of input neuron indices

SYNOPSIS ^

function InputNeurons=get_input_neurons(ThNN,CurrentNeuron)

DESCRIPTION ^

GET_INPUT_NEURONS returns array of input neuron indices

Description:
This function returns an array of input neuron indices to CurrentNeuron. 
If there is only one input argument, it gets the input neurons for the 
network instead.

Syntax:
InputNeurons=GET_INPUT_NEURONS(ThNN);
InputNeurons=GET_INPUT_NEURONS(ThNN, CurrentNeuron);

Input Parameters:
o ThNN: An object of the theta neuron network class
o CurrentNeuron: Optional index to the current neuron.

Output Parameters:
o InputNeurons: An array of indices of the input neurons to either
    CurrentNeuron or to the entire network if there is only one input
    argument.

Examples:
>> %An extra input reference neuron is added in this example
>> ThNN=theta_neuron_network('StructureFormat',{'LayerArray', [3 4 5]});
>> InputNeurons = get_input_neurons(ThNN)
>> CurrentInputNeurons = get_input_neurons(ThNN,9)

>> %The input reference neuron is removed
>> ThNN=theta_neuron_network('ReferenceTime',-1,'StructureFormat',...
     {'LayerArray', [3 4 5]});
>> InputNeurons = get_input_neurons(ThNN)
>> CurrentInputNeurons = get_input_neurons(ThNN,9)

>> %Due to recurrency, there are no strictly defined input neurons
>> ThNN=theta_neuron_network('ReferenceTime', -1, 'StructureFormat', ...
     {'ConnectionMatrix', [0 1;1 0]}, 'Io', [0.05 -0.0005]);
>> InputNeurons = get_input_neurons(ThNN)

See also theta_neuron_network, verbose

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function InputNeurons=get_input_neurons(ThNN,CurrentNeuron)
0002 %GET_INPUT_NEURONS returns array of input neuron indices
0003 %
0004 %Description:
0005 %This function returns an array of input neuron indices to CurrentNeuron.
0006 %If there is only one input argument, it gets the input neurons for the
0007 %network instead.
0008 %
0009 %Syntax:
0010 %InputNeurons=GET_INPUT_NEURONS(ThNN);
0011 %InputNeurons=GET_INPUT_NEURONS(ThNN, CurrentNeuron);
0012 %
0013 %Input Parameters:
0014 %o ThNN: An object of the theta neuron network class
0015 %o CurrentNeuron: Optional index to the current neuron.
0016 %
0017 %Output Parameters:
0018 %o InputNeurons: An array of indices of the input neurons to either
0019 %    CurrentNeuron or to the entire network if there is only one input
0020 %    argument.
0021 %
0022 %Examples:
0023 %>> %An extra input reference neuron is added in this example
0024 %>> ThNN=theta_neuron_network('StructureFormat',{'LayerArray', [3 4 5]});
0025 %>> InputNeurons = get_input_neurons(ThNN)
0026 %>> CurrentInputNeurons = get_input_neurons(ThNN,9)
0027 %
0028 %>> %The input reference neuron is removed
0029 %>> ThNN=theta_neuron_network('ReferenceTime',-1,'StructureFormat',...
0030 %     {'LayerArray', [3 4 5]});
0031 %>> InputNeurons = get_input_neurons(ThNN)
0032 %>> CurrentInputNeurons = get_input_neurons(ThNN,9)
0033 %
0034 %>> %Due to recurrency, there are no strictly defined input neurons
0035 %>> ThNN=theta_neuron_network('ReferenceTime', -1, 'StructureFormat', ...
0036 %     {'ConnectionMatrix', [0 1;1 0]}, 'Io', [0.05 -0.0005]);
0037 %>> InputNeurons = get_input_neurons(ThNN)
0038 %
0039 %See also theta_neuron_network, verbose
0040 
0041 %Copyright (C) 2008 Sam McKennoch <Samuel.McKennoch@loria.fr>
0042 
0043 
0044 if nargin == 1
0045     InputNeurons=ThNN.InputNeurons;
0046 else
0047     InputNeurons=find(ThNN.Weights(:,CurrentNeuron)~=0);
0048 end
0049 return;

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