Boolean function minimization / reduction

Hi All,

I am working on explanation of neural networks for computer security. Specifically, I would like to combine several alternative explanations together in one logical formula. I would like to ask, if anyone has experience with methods for reduction of boolean expressions. I have found these two algorithms


and

but I have not find any easy implementation in Julia. I do not know, as this topic is still of an interest, as these two methods solves problems in design of circuits.

I will appreciate and suggestions and links to resource (papers and other methods).

Thanks a lot,
Tomas

You could start with the following Python functions using PyCall:

  1. Sympy: Logic — SymPy 1.9 documentation
  2. PyEDA: Two-level Logic Minimization — Python EDA Documentation

Great, thanks a lot. I have already tried sympy through webapi, but it has failed. I am curious to try espresso through PyEDA. Thanks a lot for pointing me to this. I am impressed that almost after two years, the question got answered.

By chance, I was trying to get Sympy or PyEDA working on Windows 10. Managed to get Sympy’s SOPform example working after a little effort. But, struggling to pip install PyEDA in the Python environment on Windows 10, which apparently is not so straightforward as on Macs.

Thanks for sharing,

I am the mac and linux.

Tomas