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: