Low complexity linear decomposition at the disjoint cubes domain

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Abstract

Linear decomposition proved to be efficient technique for reducing the number of terms and literal of two-level implementation of logic functions. The decomposed system consists of linear function followed by nonlinear function of minimal realization cost. The complexity of determining the linear part makes this approach inapplicable for systems of large number of inputs when represented by truth table or decision diagrams. This paper presents a method for linearization of systems represented as a set of disjoint cubes. The reduction in complexity is achieved by a) calculation of the autocorrelation function on the disjoint cubes domain; b) representing the linear part as a superposition of linear transforms of a special form. Experimental benchmark results allow comparing the proposed technique with known linearization methods, and show the high efficiency of the proposed approach.
Original languageAmerican English
Title of host publicationProceedings of the 5th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications. World Scientific and Engineering Academy and Society (WSEAS)
StatePublished - 2006

Bibliographical note

Place of conference:Spain

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