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@ -11,6 +11,56 @@ |
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@section neuro-intro Overview |
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@subsection nature Natural Neural Network |
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From <a href="https://en.wikipedia.org/wiki/Neuron">Wikipedia</a>: |
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«A neuron is an electrically excitable cell that processes and |
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transmits information through electrical and chemical |
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signals. These signals between neurons occur via synapses, |
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specialized connections with other cells. Neurons can connect to |
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each other to form neural networks. Neurons are the core |
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components of the brain and spinal cord of the central nervous |
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system, and of the ganglia of the peripheral nervous system.» The |
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neuron connects with dendrites to the world or to the axon of |
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other neuirons. The neurites (dendrite or axon) transport |
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electrical stimulation to the cell, which emits the signal to the |
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dendrites if the activation reaches a certain level. |
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@dot |
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digraph g { |
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rankdir=LR; |
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ranksep=0.8; |
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node [shape=hexagon]; |
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edge [arrowhead=none]; |
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subgraph clusterInput { |
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label="sensors"; |
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color="white"; |
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node [shape=point]; |
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I0; I1; I2; I3; I4; I5; I6; I7; I8 I9; |
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} |
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subgraph clusterOutput { |
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label="actors"; |
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color="white"; |
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node [shape=point]; |
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O0; O1; O2; O3; O4; O5; O6; |
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} |
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I1 -> Cell1 [label="axon";taillabel="synapse"]; |
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{ I2; I3; I4; } -> Cell1; |
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{ I5; I6; I7; I8; } -> Cell2; |
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{ I4; I6; I9; I0; } -> Cell3; |
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Cell1 -> Cell8 [label="axon / dendrite"]; |
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Cell1 -> { Cell2; Cell4; Cell5; } |
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Cell2 -> { Cell4; Cell5; Cell6; Cell8; } |
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Cell3 -> { Cell4; Cell6; Cell7; Cell8; } |
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{ Cell4; Cell5; Cell6 } -> { Cell7; Cell8; } |
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Cell7 -> { O0; O1; O2 }; |
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Cell8 -> { O3; O4; O5; }; |
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Cell8 -> O6 [label="dendrite"]; |
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} |
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@enddot |
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@subsection art Artificial Neural Network |
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A complex neural network can be imitiated as a vector @c I of @c i |
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input values, a vector @c O of @c o output values and any number |
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@c l of hidden layers, where each of them contains @c h |
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@ -67,26 +117,12 @@ |
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Ox [label=<O<SUB>…</SUB>>]; |
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Oo [label=<O<SUB>o</SUB>>]; |
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} |
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I1 -> { H11; H12; H1x; H1h; } |
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I2 -> { H11; H12; H1x; H1h; } |
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Ix -> { H11; H12; H1x; H1h; } |
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Ii -> { H11; H12; H1x; H1h; } |
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H11 -> { H21; H22; H2x; H2h; } |
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H12 -> { H21; H22; H2x; H2h; } |
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H1x -> { H21; H22; H2x; H2h; } |
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H1h -> { H21; H22; H2x; H2h; } |
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H21 -> { Hx1; Hx2; Hxx; Hxh; } |
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H22 -> { Hx1; Hx2; Hxx; Hxh; } |
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H2x -> { Hx1; Hx2; Hxx; Hxh; } |
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H2h -> { Hx1; Hx2; Hxx; Hxh; } |
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Hx1 -> { Hl1; Hl2; Hlx; Hlh; } |
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Hx2 -> { Hl1; Hl2; Hlx; Hlh; } |
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Hxx -> { Hl1; Hl2; Hlx; Hlh; } |
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Hxh -> { Hl1; Hl2; Hlx; Hlh; } |
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Hl1 -> { O1; O2; Ox; Oo; } |
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Hl2 -> { O1; O2; Ox; Oo; } |
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Hlx -> { O1; O2; Ox; Oo; } |
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Hlh -> { O1; O2; Ox; Oo; } |
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{ I1; I2; Ix; Ii; } |
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-> { H11; H12; H1x; H1h; } |
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-> { H21; H22; H2x; H2h; } |
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-> { Hx1; Hx2; Hxx; Hxh; } |
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-> { Hl1; Hl2; Hlx; Hlh; } |
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-> { O1; O2; Ox; Oo; } |
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} |
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@enddot |
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@ -110,7 +146,15 @@ |
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@endcode |
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@section neuro-backward Back Propagation |
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@page biblio Bibliography |
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- <a href="http://www.tornau.name/wp-content/uploads/2009/04/studiumsmaterialien/neuronale_netze_zusammefassung.pdf">Vorlesung Neuronale Netze - Zusammenfassung - Christoph Tornau</a> |
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- <a href="http://www.neuronalesnetz.de/">Neuronale Netze — Eine Einführung</a> |
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- <a href="http://alphard.ethz.ch/hafner/Vorles/Optim/ANN/Artificial%20Neural%20Network%20based%20Curve%20Prediction%20Documentation.pdf">Artificial Neural Network based Curve Prediction</a> |
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- <a href="http://cs231n.github.io/convolutional-networks/">Convolutional Neural Networks (CNNs / ConvNets)</a> |
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- <a href="https://www.tensorflow.org/versions/r0.9/tutorials/index.html">TensorFlow utorials</a> |
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- <a href="http://alphard.ethz.ch/hafner/Vorles/Optim/ANN/Artificial%20Neural%20Network%20based%20Curve%20Prediction%20Documentation.pdf">Artificial Neural Network based Curve Prediction</a> |
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*/ |
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template |
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