Motivation: The K-Map minimizers I found over the net had an upper limit to the no: of variables they could handle in a Boolean expression. I could not grasp why something that’s based on an axiom as simple as X+X'=1 has not been generalized for n variables, where n is arbitrarily large.
On closer examination I found what kept us from finding a generalized solution. Often we look at things not as they are but as we are. We (humans) follow a Top to Bottom approach to solve Karnaugh Maps i.e. finding patterns on a '0' '1' matrix. That’s not how computers need to solve it. K-Maps are visual aids for humans, which are redundant for computers. Here I present a Bottom-up approach at solving a Boolean function which treats minterms as elements that "mate" to evaluate the function. A pdf elaborating my approach can be found here.
On closer examination I found what kept us from finding a generalized solution. Often we look at things not as they are but as we are. We (humans) follow a Top to Bottom approach to solve Karnaugh Maps i.e. finding patterns on a '0' '1' matrix. That’s not how computers need to solve it. K-Maps are visual aids for humans, which are redundant for computers. Here I present a Bottom-up approach at solving a Boolean function which treats minterms as elements that "mate" to evaluate the function. A pdf elaborating my approach can be found here.
