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Designing And Implementing A Neural Network Library For Handwriting Detection, Image Analysis etc.- The BrainNet Library - Full Code, Simplified Theory, Full Illustration, And Examples

, 21 Oct 2009 CPOL
This article will explain the actual concepts and implementation of Backward Propagation Neural Networks very easily - see project code and samples, like a simple pattern detector, a hand writing detection pad, an xml based neural network processing language etc in the source zip.
brainnet_src.zip
BrainNetIntro
NeuralGate
NeuralGate.vbproj.user
PatternDetector
PatternDetector.vbproj.user
TestImages
a1.bmp
b1.bmp
b2.bmp
c1.bmp
c2.bmp
D.bmp
D1.bmp
D2.bmp
E1.bmp
E2.bmp
Thumbs.db
Framework
BrainNet.suo
NetworkDataModel
Network.xsx
NeuralXML.xsx
NetworkIO.xsx
NeuralFramework.vbproj.user
nxml
nxml.vbproj.user
BrainNet.suo
Doc
Documentation.chm
Samples
HandWriting
HandWriting.suo
HandWriting.vbproj.user
'------------------------------------------------------------------
' License Notice:
'------------------------------------------------------------------
' All Rights Reserved - Anoop Madhusudanan, 
' Mail: amazedsaint@gmail.com
' Website: http://amazedsaint.blogspot.com

' See my articles about BrainNet at 
' http://amazedsaint-articles.blogspot.com for details
'
' You can use this code (or part of it), for non 
' commercial and academic uses, as long as 
'   - You are keeping this notice along with it
'   - You are not making any profit out of this
'------------------------------------------------------------------

Public Interface INeuralNetwork

    '''<summary>Method to train a network </summary>    
    Sub TrainNetwork(ByVal t As TrainingData)
    '''<summary>This function can be used for connecting two neurons together </summary>
    Sub ConnectNeurons(ByVal source As INeuron, ByVal destination As INeuron, ByVal weight As Single)
    '''<summary>This function can be used for connecting two neurons together with random weight </summary>
    Sub ConnectNeurons(ByVal source As INeuron, ByVal destination As INeuron)
    '''<summary>This function can be used for connecting neurons in two layers together with random weights </summary>
    Sub ConnectLayers(ByVal layer1 As NeuronLayer, ByVal layer2 As NeuronLayer)
    '''<summary>This function can be used for connecting all layers together </summary>
    Sub ConnectLayers()
    '''<summary>This function may be used for running the network </summary>
    Function RunNetwork(ByVal inputs As ArrayList) As ArrayList
    '''<summary>This function may be used to obtain the output list </summary>
    Function GetOutput() As ArrayList
    ReadOnly Property Layers() As NeuronLayerCollection
    '''<summary>Gets the first (input) layer</summary>
    ReadOnly Property InputLayer() As NeuronLayer
    '''<summary>Gets the last (output) layer</summary>
    ReadOnly Property OutputLayer() As NeuronLayer

End Interface

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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