documentation updated
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@@ -171,12 +171,13 @@ AC_DEFUN([AX_INIT_STANDARD_PROJECT], [
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AX_SUBST(NUMBERS)
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AX_SUBST(NUMBERS)
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AX_SUBST(HOME)
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AX_SUBST(HOME)
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if test -f README.md; then
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if test -f README.md; then
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README=$()
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README=$(tail -n +3 README.md)
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DESCRIPTION=$(head -1 README.md)
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DESCRIPTION=$(head -1 README.md)
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else
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else
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README=$(tail -n +3 README)
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README=$(tail -n +3 README)
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DESCRIPTION=$(head -1 README)
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DESCRIPTION=$(head -1 README)
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fi
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fi
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README_ESCAPED=$(echo "$README" | sed ':a;N;$!ba;s/\n/\\n/g;s,",\\",g')
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if which pandoc 2>&1 > /dev/null; then
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if which pandoc 2>&1 > /dev/null; then
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README_HTML=$(echo "$README" | pandoc -f markdown_github -t html | sed ':a;N;$!ba;s,\\\(.\),\\\\<span>\1</span>,g;s/\n/\\n/g;s,",\\",g;s, ,\ \ ,g')
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README_HTML=$(echo "$README" | pandoc -f markdown_github -t html | sed ':a;N;$!ba;s,\\\(.\),\\\\<span>\1</span>,g;s/\n/\\n/g;s,",\\",g;s, ,\ \ ,g')
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else
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else
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@@ -184,6 +185,8 @@ AC_DEFUN([AX_INIT_STANDARD_PROJECT], [
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fi
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fi
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AX_SUBST(README)
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AX_SUBST(README)
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_AM_SUBST_NOTMAKE([README])
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_AM_SUBST_NOTMAKE([README])
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AX_SUBST(README_ESCAPED)
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_AM_SUBST_NOTMAKE([README_ESCAPED])
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AX_SUBST(README_HTML)
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AX_SUBST(README_HTML)
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_AM_SUBST_NOTMAKE([README_HTML])
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_AM_SUBST_NOTMAKE([README_HTML])
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AX_SUBST(DESCRIPTION)
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AX_SUBST(DESCRIPTION)
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@@ -529,7 +529,11 @@ ${DEFAULT_PROJECT_NAME}
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add description for ${DEFAULT_PROJECT_NAME}
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add description for ${DEFAULT_PROJECT_NAME}
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EOF
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EOF
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to configure.ac <<EOF && notice "please edit configure.ac, then rerun $0" && exit 0
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to configure.ac <<EOF && notice "please edit configure.ac, then rerun $0" && exit 0
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${HEADER}m4_define(x_package_name, ${DEFAULT_PROJECT_NAME}) # project's name
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${HEADER}# default is generated from AUTHORS and project name
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PROJECT_URL=
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SOURCE_DOWNLOAD=
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m4_define(x_package_name, ${DEFAULT_PROJECT_NAME}) # project's name
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m4_define(x_major, 0) # project's major version
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m4_define(x_major, 0) # project's major version
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m4_define(x_minor, 0) # project's minor version
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m4_define(x_minor, 0) # project's minor version
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m4_include(ax_init_standard_project.m4)
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m4_include(ax_init_standard_project.m4)
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@@ -1,5 +1,16 @@
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#titlearea {
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#titlearea {
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display: flex;
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display: flex;
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justify-content: space-between;
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justify-content: space-between;
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align-items: flex-end;
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align-items: flex-begin;
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}
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#titlearea nav {
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padding: 0;
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margin: 0;
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}
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#titlearea nav a {
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background-color: lightgray;
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border: 1px solid gray;
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color: black;
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padding: 1ex;
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margin: 0;
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}
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}
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@@ -11,6 +11,56 @@
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@section neuro-intro Overview
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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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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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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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@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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Ox [label=<O<SUB>…</SUB>>];
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Oo [label=<O<SUB>o</SUB>>];
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Oo [label=<O<SUB>o</SUB>>];
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}
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}
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I1 -> { H11; H12; H1x; H1h; }
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{ I1; I2; Ix; Ii; }
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I2 -> { H11; H12; H1x; H1h; }
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-> { H11; H12; H1x; H1h; }
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Ix -> { H11; H12; H1x; H1h; }
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-> { H21; H22; H2x; H2h; }
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Ii -> { H11; H12; H1x; H1h; }
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-> { Hx1; Hx2; Hxx; Hxh; }
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H11 -> { H21; H22; H2x; H2h; }
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-> { Hl1; Hl2; Hlx; Hlh; }
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H12 -> { H21; H22; H2x; H2h; }
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-> { O1; O2; Ox; Oo; }
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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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}
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}
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@enddot
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@enddot
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@@ -110,7 +146,15 @@
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@endcode
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@endcode
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@section neuro-backward Back Propagation
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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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*/
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template
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template
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