php/neuronics/neural.php

   1 #!/usr/bin/php
   2 <?php
   3 //NMNN - Nervous Man's Neural Network
   4 //Harvie 2oo7/8
   5 /*
   6  * My first neural network
   7  */
   8
   9 ///SETTINGS/INIT
  10 $nmnn_version = '0.1-DEV';
  11
  12
  13 ///FUNCTIONS///////////////////////////////////////////////////////////////////////////////////////
  14
  15 function nervous_banner($text) { //Print banner with custom text
  16         echo("\n[*]-== Nervous Man's Neural Network ==-[*]\n");
  17         $text = explode("\n", $text);
  18         foreach($text as $line) {
  19                 $line = trim($line);
  20                 echo("                                     =-[+]\r");
  21                 echo("[+]-= $line\n");
  22         }
  23         echo("[*]-==================================-[*]\n\n");
  24 }
  25
  26 function neural_network_create($net) { //Create new network in $GLOBALS['neural_networks'][$net]
  27         if(isset($GLOBALS['neural_networks'][$net])) {
  28                 echo("Net already exists\n");
  29                 return(0);
  30         }
  31         $GLOBALS['neural_networks'][$net] = new neural_network($net);
  32         return(1);
  33 }
  34
  35 function neural_network($net) {
  36         return($GLOBALS['neural_networks'][$net]);
  37 }
  38
  39 function global_neuron($net, $id) {
  40         return neural_network($net)->neurons[$id];
  41 }
  42
  43 ///CLASSES/////////////////////////////////////////////////////////////////////////////////////////
  44
  45 class neuron { //Single Neurone class
  46
  47         var $net = 'N/A'; //ID of network containing this neuron
  48         var $id = 'N/A'; //ID of this neuron
  49         var $treshold = 0; //Treshold is sensitivity of this neuron
  50         var $synapses = array(); //List of neurons connected to dendrites (inputs)
  51         var $decisions = array(); //List of values received from dendrites
  52         var $axon = 'N/A'; //Final decision of this neuron
  53         var $sensor = false; //Is this a sensor?
  54
  55         function neuron($net, $id, $treshold=0) { //Constructor - Set neuron identification
  56                 $this->net = $net;
  57                 $this->id = $id;
  58                 $this->treshold = $treshold;
  59         }
  60
  61         function synapse_add($id, $strength=0) { //Connect neuron to dendrite
  62                 $this->synapses[$id] = $strength;
  63         }
  64
  65         function synapse_request($id) { //Request synapse add by another neuron
  66                 if(!is_array($id)) {
  67                         global_neuron($this->net, $id)->synapse_add($this->id);
  68                 } else foreach($id as $id_single) {
  69                         global_neuron($this->net, $id_single)->synapse_add($this->id);
  70                 }
  71         }
  72
  73         function synapse_break($id) { //Disconnect neuron from dendrite
  74                 unset($this->synapses[$id]);
  75         }
  76
  77         function debug() { //Print info about this neuron
  78                 echo("[i] Info about neuron no.$this->id in $this->net network:\n");
  79                 if($this->sensor) { //if this is sensor print different stuff
  80                         echo("\tThis cell is a SENSOR!!!\n\tSensor axon value:$this->axon\n\n");
  81                         return('s');
  82                 }
  83                 echo("\tTreshold: $this->treshold\n\tAxon: $this->axon\n");
  84                 echo("\tSynapses:\n");
  85                 print_r($this->synapses);
  86                 echo("\tDecisions:\n");
  87                 print_r($this->decisions);
  88                 echo("\n");
  89         }
  90
  91         function dendrites_read() { //Receive axon values from all neurons connected to dendrites
  92                 if($this->sensor) return('s');
  93                 $this->decisions = array(); //Remove old decisions
  94                 foreach($this->synapses as $synapse => $strength) {
  95                         //print_r (global_neuron($this->net, $synapse)); //debug
  96                         global_neuron($this->net, $synapse)->dendrites_read();
  97                         global_neuron($this->net, $synapse)->decide();
  98                         $this->decisions[$synapse]=global_neuron($this->net, $synapse)->axon_get();
  99                 }
 100         }
 101
 102         function decide() { //Decide final axon (output) value - read dendrites first!
 103                 if($this->sensor) return('s');
 104                 $this->axon = 0; //Reset old
 105                 foreach($this->decisions as $synapse => $decision) {
 106                         $this->axon += $decision * $this->synapses[$synapse];
 107                 }
 108                 if($this->axon > $this->treshold) {
 109                         $this->axon = 1;
 110                 } else {
 111                         $this->axon = 0;
 112                 }
 113         }
 114
 115         function axon_get() {
 116                 return $this->axon;
 117         }
 118
 119         function learn($truth) { //Determine, what is truth
 120                 if($this->sensor) return('s');
 121                 foreach($this->decisions as $synapse => $decision) {
 122                         if($decision == $truth) {
 123                                 $this->synapses[$synapse]++;
 124                         } else {
 125                                 $this->synapses[$synapse]--;
 126                         }
 127                 }
 128         }
 129
 130         function sensor_set($sensor_value, $is_sensor=true) { //Make sensor from this neuron and set axon value
 131                 $this->sensor = $is_sensor;
 132                 $this->axon = $sensor_value;
 133         }
 134
 135 }
 136
 137
 138
 139 class neural_network { //Single neural network class
 140
 141         var $net = 'N/A'; //Name of this network
 142         var $neurons = array(); //Array of neuron objects
 143
 144         function neural_network($net) { //Constructor - Set network name
 145                 $this->net = $net;
 146         }
 147
 148         function add_neuron($id, $treshold=0) { //Creates new neurone with specified id
 149                 if(!isset($this->neurons[$id])) {
 150                         $this->neurons[$id] = new neuron($this->net, $id, $treshold);
 151                 } else return(0);
 152         }
 153
 154         function debug() { //Print debug for all neurons in network
 155                 echo("###########\nDebug information about $this->net network:\n###########\n\n");
 156                 foreach($this->neurons as $neuron) $neuron->debug();
 157         }
 158
 159         function learn($truth) { //Learn all neurons
 160                 foreach($this->neurons as $neuron) $neuron->learn($truth);
 161         }
 162
 163 }
 164
 165 ///BANNER
 166 nervous_banner("\nNeural network simulator\nCoded by Harvie 2oo7/8\nInfo:\n- Version: $nmnn_version\n- NeuroNet library loaded!\n");
 167
 168 /*
 169                 8x ---------------------------------- CUT HERE ----------------------------------
 170  */
 171
 172 ///SAMPLE_NETWORK///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
 173
 174 neural_network_create('neuronet'); //Create new network called neuronet
 175 for($i=1;$i<=6;$i++) neural_network('neuronet')->add_neuron($i,-1); //Create few neurons in neuronet
 176
 177 /*
 178         Now wee have six neurons floating somewhere in the network space:
 179
 180         (1) (2) (3) (4) (5) (6)
 181  */
 182
 183 //Connect neurons into synapse infrastructure:
 184 global_neuron('neuronet', 1)->synapse_request(array(3,4));
 185 global_neuron('neuronet', 2)->synapse_request(array(4,5));
 186 global_neuron('neuronet', 3)->synapse_request(6);
 187 global_neuron('neuronet', 4)->synapse_request(6);
 188 global_neuron('neuronet', 5)->synapse_request(6);
 189
 190 //Convert neurons 1 and 2 to sensors:
 191 for($i=1;$i<=2;$i++) global_neuron('neuronet', $i)->sensor_set(0, true);
 192
 193
 194 /*
 195         After making this synapse infrastructure, we'll get somethinq like this:
 196
 197                         _(3)_
 198              /-->  ]1)_/     \
 199         Input          \_(4)__\_(6> -> Output
 200              \-->  ]2)_/      /
 201                        \_(5)_/
 202
 203         ]1) and ]2) are sensors/receptors/...
 204         (6> is output
 205
 206         Network structure inspired by: http://en.wikipedia.org/wiki/Image:Neural_network_example.png
 207
 208         If you can't understand this, i can try to say it easier: "It's something like your brain (but much more complicated)" ;D
 209         Or try to read one of these:
 210                 - http://en.wikipedia.org/wiki/Neural_networks
 211                 - http://en.wikipedia.org/wiki/Artificial_neural_network
 212
 213  */
 214
 215 //Now, i have neural network and i will try to teach it something
 216
 217 /*
 218
 219         I will try to teach this network to compare two booleans
 220         Epected output values:
 221                 INPUT   |       OUTPUT
 222                 0,0     |       1
 223                 1,1     |       1
 224                 0,1     |       0
 225                 1,0     |       0
 226
 227         So. Let's try to write some function for this:
 228
 229 */
 230
 231 function same($first, $second) { //This function uses neural network to compare two bools
 232
 233         global_neuron('neuronet', 1)->sensor_set($first);
 234         global_neuron('neuronet', 2)->sensor_set($second);
 235
 236         global_neuron('neuronet', 6)->dendrites_read();
 237         global_neuron('neuronet', 6)->decide();
 238         $decision = global_neuron('neuronet', 6)->axon_get();
 239
 240         echo("$first == $second ?\nnetwork says: $decision (0=NO, 1=YES)\n");
 241
 242         return($decision);
 243 }
 244
 245 /*
 246
 247         We got nice function (in fact it hardly sux, like whole this network...)
 248         How to use it?:
 249
 250 */
 251
 252 ///Learning:
 253
 254 same(0,0); //Ask
 255 neural_network('neuronet')->learn('true'); //Correct answer (teach)
 256 neural_network('neuronet')->learn('true'); //Correct answer (teach)
 257 same(1,0);
 258 neural_network('neuronet')->learn('false');
 259 neural_network('neuronet')->learn('false');
 260 same(0,1);
 261 neural_network('neuronet')->learn('false');
 262 neural_network('neuronet')->learn('false');
 263
 264 ///Using superinteligent lifeform ehm... 3 neurones brain ;P
 265
 266 echo("\nI hope it will work now: 8')\n\n");
 267 same(0,0); //Ask (without teaching)
 268
 269 //Now, we like to print some stats
 270 neural_network('neuronet')->debug(); //Print some info about neuronet and it's neurons
 271
 272