Implication

Patterns

Applicable neurons

• NOT
• OR
• AND
• XOR
• NAND
• NOR
• IF
• Rectangle - circuit
• begin of start tag
• tag div
• x × (-1)
• >, < opposite

Algorithm

Test

/**
 * 1: 
 *
 * @return {Array}
 */
function neuron501()
{
return [1];
}

/**
 * Minus (x - y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron2(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '-'+Number(x2)).toString()];
}

/**
 * NOT: 
 * 
 * @param x1 1/0
 * @return {Array}
 */
function neuron567(x1)
{
  var outputs = [];
  outputs[0] = x1;

  arr = neuron501();
  outputs[1] = arr[0];

  arr = neuron2(outputs[1], outputs[0]);
  outputs[2] = arr[0];

  return[outputs[2]];
}


/**
 * Multiple (x × y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron3(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '*'+Number(x2)).toString()];
}

/**
 * 1: 
 *
 * @return {Array}
 */
function neuron501()
{
return [1];
}

/**
 * Minus (x - y): 
 *
 * @param x1 Number X
 * @param x2 Number Y
 * @return {Array}
 */
function neuron2(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '-'+Number(x2)).toString()];
}

/**
 * NAND: 
 * 
 * @param x1 1/0
 * @param x2 1/0
 * @return {Array}
 */
function neuron572(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron3(outputs[0], outputs[1]);
  outputs[2] = arr[0];

  arr = neuron501();
  outputs[3] = arr[0];

  arr = neuron2(outputs[3], outputs[2]);
  outputs[4] = arr[0];

  return[outputs[4]];
}


/**
 * Implication: 
 * 
 * @param x1 A (1/0)
 * @param x2 B (1/0)
 * @return {Array}
 */
function neuron597(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron567(outputs[1]);
  outputs[2] = arr[0];

  arr = neuron572(outputs[2], outputs[0]);
  outputs[3] = arr[0];

  return[outputs[3]];
}