The following is a pattern recognition engine based on the Hopfield Neural Network.

Before running any of the code in this repo, the following must be installed at the minimum:

• Python 3.6.4
• Numpy version 1.14.0
• Tkinter version 8.6
• Argparse version 1.4.0

• README.md
• hopfiled.py
• testHopfield.py

Program supports commandline interface which allows to run with variable number of row and columns and the visiting order for the hopfiled algorithm.

-h, --help		show this help message and exit
-r ROW, --row ROW 	Number of rows for the pattern engine (int)
-c COL, --col COL 	Number of columns for the pattern engine (int)
-o [ORDER [ORDER ...]], --order [ORDER [ORDER ...]]
			List specifying visiting order of each node

By default, the pattern engine contains 4 rows and 4 columns with random visiting order. To run the program with default setting, use python ./testHopfield.py.

To run the program with 4 rows and 5, use python ./testHopfield.py -r 4 -c 5

Size of the list specifying order must exactly be equal to row * column. Furthermore, each of the element in the order list must be unique, ranging from 0 to [(row * col) - 1].

For example, if the pattern machine has 4 row and 3 column, then the size of the order list must be 4 * 3 = 12 element. The following is one possible combination:

python .\testHopfield.py -r 4 -c 3 -o 0 2 4 6 8 10 1 3 5 7 9 11

If the size of the order list does not match row * column or the element of the list does not satisfy the ranging criteria, then order list will be randomized to a new valid list.

• Add additional features to GUI

• Ravi Patel: https://github.com/rpatel26