Inputs

1. complex issue  the real number (a from "a+bi")

1. complex number  imaginary unit (b from "a+bi")

2. complex issue  the real number (a from "a+bi")

2. complex number  imaginary unit (b from "a+bi")
Outputs

real number (a from "a+bi")

imaginary unit (b from "a+bi")
Neuron type
Best algorithm has been found  locked
Patterns
Pattern 
Input 
Output 
1 
1. complex issue  the real number (a from "a+bi"): 
5 
1. complex number  imaginary unit (b from "a+bi"): 
8 
2. complex issue  the real number (a from "a+bi"): 
7 
2. complex number  imaginary unit (b from "a+bi"): 
2 

real number (a from "a+bi"): 
12 
imaginary unit (b from "a+bi"): 
10 

2 
1. complex issue  the real number (a from "a+bi"): 
1 
1. complex number  imaginary unit (b from "a+bi"): 
1 
2. complex issue  the real number (a from "a+bi"): 
1 
2. complex number  imaginary unit (b from "a+bi"): 
1 

real number (a from "a+bi"): 
2 
imaginary unit (b from "a+bi"): 
2 

3. 
1. complex issue  the real number (a from "a+bi"): 
1 
1. complex number  imaginary unit (b from "a+bi"): 
2 
2. complex issue  the real number (a from "a+bi"): 
3 
2. complex number  imaginary unit (b from "a+bi"): 
4 

real number (a from "a+bi"): 
4 
imaginary unit (b from "a+bi"): 
6 

Applicable neurons

Plus (x + y)
Algorithm
Test
Code made by AI:
/**
* Plus (x + y): The addition of two whole numbers is the total amount of those quantities combined.
*
* @param x1 first number
* @param x2 second number
* @return {Array}
*/
function neuron1(x1, x2)
{
math.config({number: 'BigNumber', precision: 64}); return [math.eval(Number(x1) + '+'+Number(x2)).toString()];
}
/**
* Sum of complex numbers:
*
* @param x1 1. complex issue  the real number (a from "a+bi")
* @param x2 1. complex number  imaginary unit (b from "a+bi")
* @param x3 2. complex issue  the real number (a from "a+bi")
* @param x4 2. complex number  imaginary unit (b from "a+bi")
* @return {Array}
*/
function neuron4(x1, x2, x3, x4)
{
var outputs = [];
outputs[0] = x1;
outputs[1] = x2;
outputs[2] = x3;
outputs[3] = x4;
arr = neuron1(outputs[0], outputs[2]);
outputs[4] = arr[0];
arr = neuron1(outputs[1], outputs[3]);
outputs[5] = arr[0];
return[outputs[4], outputs[5]];
}
Code made by AI: