1. Learning Combinational Logic
ECE 539 Final Project
Marcel Wermeckes

2. Boolean equation input
User enters boolean equations
Number of equations can be very large
Number of input variables arbitrary
Examples:
F=A+B&(!C)+(B^D)&A
G=B&C^(!(D&A))

3. Boolean functions supported
AND &
OR +
XOR ^
NOT !
Program follows precedence rules:
A+B&D = A+(B&D)
All equations must have correct parentheses

4. Training
Neural Network learns combinational logic through I/O patterns
Backpropagation Algorithm
One hidden layer
Parameters that can be set by user:
• Momentum
• Learning rate
• Number of nodes in hidden layer
• Number of training cycles/epochs

5. Testing
After being trained, program will ask user for values of input variables and computes output
Compares all output patterns of boolean equations with output generated by Neural Network
Dumps errors to a file

6. Algorithm Implementation
C++
dynamic
Type double for all calculations
Input
Hidden
Output

7. Results
A&B^C+(A&B)^A
A+((!B)+C&A)
C+B^A