Example 3

This is a later experiment I tried, with a little different perspective on the code. This example is coded in C++.

 

View maincode.h

View maincode.cpp

View cART1.h

View cART1.cpp

 

Example Results 1

Vigilance = 0.3

-----------------------------------------------------
Active Neuron: 0
Input:  1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Output: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,

-----------------------------------------------------
Active Neuron: 1
Input:  0 1 0 0 1 0 0 1 0 0 1 0 0 1 0
Output: 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,

-----------------------------------------------------
Active Neuron: 0
Input:  1 0 1 1 0 1 1 1 1 1 0 1 1 0 1
Output: 1 0 1 1 0 0 1 0 0 1 0 0 1 0 1

Top-down weights:
1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,

Bottom-up weights:
0.25, 0, 0.25, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0.25,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,

-----------------------------------------------------
Active Neuron: 2
Input:  0 1 0 1 0 1 1 0 1 1 0 1 0 1 0
Output: 0 1 0 1 0 1 1 0 1 1 0 1 0 1 0

Top-down weights:
1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0,

Bottom-up weights:
0.25, 0, 0.25, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0.25,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0, 0.22, 0, 0.22, 0, 0.22, 0.22, 0, 0.22, 0.22, 0, 0.22, 0, 0.22, 0,

-----------------------------------------------------
Active Neuron: 0
Input:  1 1 1 1 0 1 1 0 0 1 0 0 1 1 1
Output: 1 0 1 1 0 0 1 0 0 1 0 0 1 0 1

Top-down weights:
1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0,

Bottom-up weights:
0.25, 0, 0.25, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0.25,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0, 0.22, 0, 0.22, 0, 0.22, 0.22, 0, 0.22, 0.22, 0, 0.22, 0, 0.22, 0,

-----------------------------------------------------
Active Neuron: 0
Input:  0 1 1 1 0 0 1 0 0 1 0 0 0 1 1
Output: 0 0 1 1 0 0 1 0 0 1 0 0 0 0 1

Top-down weights:
0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0,

Bottom-up weights:
0, 0, 0.33, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0, 0, 0.33,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0, 0.22, 0, 0.22, 0, 0.22, 0.22, 0, 0.22, 0.22, 0, 0.22, 0, 0.22, 0,

 

Example Results 2

Vigilance = 0.8

-----------------------------------------------------
Active Neuron: 0
Input:  1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Output: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,

-----------------------------------------------------
Active Neuron: 1
Input:  0 1 0 0 1 0 0 1 0 0 1 0 0 1 0
Output: 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,

-----------------------------------------------------
Active Neuron: 2
Input:  1 0 1 1 0 1 1 1 1 1 0 1 1 0 1
Output: 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0.17, 0, 0.17, 0.17, 0, 0.17, 0.17, 0.17, 0.17, 0.17, 0, 0.17, 0.17, 0, 0.17,

-----------------------------------------------------
Active Neuron: 3
Input:  0 1 0 1 0 1 1 0 1 1 0 1 0 1 0
Output: 0 1 0 1 0 1 1 0 1 1 0 1 0 1 0

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,
0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0.17, 0, 0.17, 0.17, 0, 0.17, 0.17, 0.17, 0.17, 0.17, 0, 0.17, 0.17, 0, 0.17,
0, 0.22, 0, 0.22, 0, 0.22, 0.22, 0, 0.22, 0.22, 0, 0.22, 0, 0.22, 0,

-----------------------------------------------------
Active Neuron: 0
Input:  1 1 1 1 0 1 1 0 0 1 0 0 1 1 1
Output: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1

Top-down weights:
1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,
0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0,

Bottom-up weights:
0.2, 0.2, 0.2, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0, 0, 0.2, 0.2, 0.2,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0.17, 0, 0.17, 0.17, 0, 0.17, 0.17, 0.17, 0.17, 0.17, 0, 0.17, 0.17, 0, 0.17,
0, 0.22, 0, 0.22, 0, 0.22, 0.22, 0, 0.22, 0.22, 0, 0.22, 0, 0.22, 0,

-----------------------------------------------------
Active Neuron: 0
Input:  0 1 1 1 0 0 1 0 0 1 0 0 0 1 1
Output: 0 1 1 1 0 0 1 0 0 1 0 0 0 1 1

Top-down weights:
0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1,
0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1,
0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0,

Bottom-up weights:
0, 0.25, 0.25, 0.25, 0, 0, 0.25, 0, 0, 0.25, 0, 0, 0, 0.25, 0.25,
0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0, 0, 0.33, 0,
0.17, 0, 0.17, 0.17, 0, 0.17, 0.17, 0.17, 0.17, 0.17, 0, 0.17, 0.17, 0, 0.17,
0, 0.22, 0, 0.22, 0, 0.22, 0.22, 0, 0.22, 0.22, 0, 0.22, 0, 0.22, 0,

 

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