6 research outputs found

    Universal P Systems: One Catalyst Can Be Suficient

    Get PDF
    Whether P systems with only one catalyst can already be universal, is still an open problem. Here we establish universality (computational completeness) by using speci c variants of additional control mechanisms. At each step using only multiset rules from one set of a nite number of sets of rules allows for obtaining computational completeness with one catalyst and only one membrane. If the targets are used for choosing the multiset of rules to be applied, for getting computational completeness with only one catalyst more than one membrane is needed. If the available sets of rules change periodically with time, computational completeness can be obtained with one catalyst in one membrane. Moreover, we also improve existing computational completeness results for P systems with mobile catalysts and for P systems with membrane creation.Junta de Andalucía P08 – TIC 0420

    Computational Completeness of P Systems Using Maximal Variants of the Set Derivation Mode

    Get PDF
    We consider P systems only allowing rules to be used in at most one copy in each derivation step, especially the variant of the maximally parallel derivation mode where each rule may only be used at most once. Moreover, we also consider the derivation mode where from those sets of rules only those are taken which have the maximal number of rules. We check the computational completeness proofs of several variants of P systems and show that some of them even literally still hold true for the for these two new set derivation modes. Moreover, we establish two new results for P systems using target selection for the rules to be chosen together with these two new set derivation modes

    Multi-Objective Binary PSO with Kernel P System on GPU

    Get PDF
    Computational cost is a big challenge for almost all intelligent algorithms which are run on CPU. In this regard, our proposed kernel P system multi-objective binary particle swarm optimization feature selection and classification method should perform with an efficient time that we aimed to settle via using potentials of membrane computing in parallel processing and nondeterminism. Moreover, GPUs perform better with latency-tolerant, highly parallel and independent tasks. In this study, to meet all the potentials of a membrane-inspired model particularly parallelism and to improve the time cost, feature selection method implemented on GPU. The time cost of the proposed method on CPU, GPU and Multicore indicates a significant improvement via implementing method on GPU

    Sequential P Systems with Regular Control

    No full text
    International audienceno abstrac

    Sequential P Systems with Regular Control

    No full text
    International audienceno abstrac
    corecore