Reduction of sizes of decision diagrams by autocorrelation functions

This paper discusses optimization of decisions diagrams (DDs) by total autocorrelation functions. We present an efficient algorithm for construction of linearly transformed binary decision diagrams (LT-BDDs) and Linearly transformed multiterminal BDDs (LT-MTBDDs) for systems of Boolean functions, based on linearization of these functions by the corresponding autocorrelation functions. Then, we present a method for reduction of sizes of DDs by a level-by-level reduction of the width of DDs using the total autocorrelation functions. The approach provides for a simple procedure for minimization of LT-BDDs and LT-MTBDDs and upper bounds on their sizes. Experimental results for benchmarks illustrate that the proposed method on average is very efficient.