Linear decomposition of index generation functions
Tsutomu Sasao · 2012
This paper shows a heuristic method to reduce the number of variables to represent incompletely specified index generation functions using linear decompositions. To find good linear transformations, two measures are introduced: the imbalance measure and the ambiguity measure. Experimental results using m-out-of-n code to binary converters, randomly generated functions, IP address tables, and lists of English words show the usefulness of the approach.