Search results for "Circuit minimization for Boolean functions"

showing 2 items of 2 documents

BMaD – A Boolean Matrix Decomposition Framework

2014

Boolean matrix decomposition is a method to obtain a compressed representation of a matrix with Boolean entries. We present a modular framework that unifies several Boolean matrix decomposition algorithms, and provide methods to evaluate their performance. The main advantages of the framework are its modular approach and hence the flexible combination of the steps of a Boolean matrix decomposition and the capability of handling missing values. The framework is licensed under the GPLv3 and can be downloaded freely at http://projects.informatik.uni-mainz.de/bmad.

Matrix (mathematics)Theoretical computer scienceAnd-inverter graphBoolean circuitDecomposition (computer science)Logical matrixCircuit minimization for Boolean functionsRepresentation (mathematics)Standard Boolean modelMathematics
researchProduct

Quantum Query Complexity of Boolean Functions with Small On-Sets

2008

The main objective of this paper is to show that the quantum query complexity Q(f) of an N-bit Boolean function f is bounded by a function of a simple and natural parameter, i.e., M = |{x|f(x) = 1}| or the size of f's on-set. We prove that: (i) For $poly(N)\le M\le 2^{N^d}$ for some constant 0 < d < 1, the upper bound of Q(f) is $O(\sqrt{N\log M / \log N})$. This bound is tight, namely there is a Boolean function f such that $Q(f) = \Omega(\sqrt{N\log M / \log N})$. (ii) For the same range of M, the (also tight) lower bound of Q(f) is $\Omega(\sqrt{N})$. (iii) The average value of Q(f) is bounded from above and below by $Q(f) = O(\log M +\sqrt{N})$ and $Q(f) = \Omega (\log M/\log N+ \sqrt{N…

CombinatoricsDiscrete mathematicsComplexity indexKarp–Lipton theoremBounded functionCircuit minimization for Boolean functionsCircuit complexityUpper and lower boundsPlanarity testingBoolean conjunctive queryMathematics
researchProduct