96,236 research outputs found
A weighted pair graph representation for reconstructibility of Boolean control networks
A new concept of weighted pair graphs (WPGs) is proposed to represent a new
reconstructibility definition for Boolean control networks (BCNs), which is a
generalization of the reconstructibility definition given in [Fornasini &
Valcher, TAC2013, Def. 4]. Based on the WPG representation, an effective
algorithm for determining the new reconstructibility notion for BCNs is
designed with the help of the theories of finite automata and formal languages.
We prove that a BCN is not reconstructible iff its WPG has a complete subgraph.
Besides, we prove that a BCN is reconstructible in the sense of [Fornasini &
Valcher, TAC2013, Def. 4] iff its WPG has no cycles, which is simpler to be
checked than the condition in [Fornasini & Valcher, TAC2013, Thm. 4].Comment: 20 pages, 10 figures, accepted by SIAM Journal on Control and
Optimizatio
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An Evolutionary Approach to the Design of Controllable Cellular Automata Structure for Random Number Generation
Cellular Automata (CA) has been used in pseudorandom number generation over a decade. Recent studies show that two-dimensional (2-d) CA Pseudorandom Number Generators (PRNGs) may generate better random sequences than conventional one-dimensional (1-d) CA PRNGs, but they are more complex to implement in hardware than 1-d CA PRNGs. In this paper, we propose a new class of 1-d CA Controllable Cellular Automata (CCA) without much deviation from the structure simplicity of conventional 1-d CA. We give a general definition of CCA first and then introduce two types of CCA – CCA0 and CCA2. Our initial study on them shows that these two CCA PRNGs have better randomness quality than conventional 1-d CA PRNGs but their randomness is affected by their structures. To find good CCA0/CCA2 structures for pseudorandom number generation, we evolve them using the Evolutionary Multi-Objective Optimization (EMOO) techniques. Three different algorithms are presented in this paper. One makes use of an aggregation function; the other two are based on the Vector Evaluated Genetic Algorithm (VEGA). Evolution results show that these three algorithms all perform well. Applying a set of randomness tests on the evolved CCA PRNGs, we demonstrate that their randomness is better than that of 1-d CA PRNGs and can be comparable to that of two-dimensional CA PRNGs
Positive scalar curvature on foliations: the noncompact case
Let be a noncompact enlargeable Riemannian manifold in the sense
of Gromov-Lawson and an integrable subbundle of . Let be the
leafwise scalar curvature associated to . We show that if either
or is spin, then . This generalizes earlier
claims for hyper-Euclidean spaces made by Gromov.Comment: 14 page
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