Fundamenta Informaticae - Volume 134, issue 1-2

Authors: Orellana-Martín, David | Graciani, Carmen | Macías-Ramos, Luis-Felipe | Martínez-del-Amor, Miguel Ángel | Riscos-Núñez, Agustín | Romero-Jiménez, Álvaro | Valencia-Cabrera, Luis

Article Type: Research Article

Abstract: Sevilla carpets have already been used to compare different solutions of the Subset Sum problem: either designed in the framework of P systems with active membranes (both in the case of membrane division and membrane creation), and in the framework of tissue-like P systems with cell division. Recently, the degree of parallelism and other descriptive complexity details have been found to be relevant when designing parallel simulators running on GPUs. We present here a new way to use the information provided by Sevilla carpets in this context, and a script that allows to generate them automatically from P-Lingua files.

Keywords: P systems, descriptive complexity, Sevilla carpets, P-Lingua, MeCoSim

DOI: 10.3233/FI-2014-1096

Citation: Fundamenta Informaticae, vol. 134, no. 1-2, pp. 153-166, 2014

Authors: Păun, Andrei | Sosík, Petr

Article Type: Research Article

Abstract: We improve and extend a recent result showing that spiking neural P systems with the same rules in all neurons of the system (homogenous) and working in the max sequential manner are universal. The previous work in this area reported by the group led by Dr. Linqiang Pan did not put any bound on the number of neurons used. We believe this is an important question for any future practical implementation of such systems that deserves investigation, and we provide some results in this direction. Extending the aforementioned construction with the work of Korec on small register machines one could …estimate the size of the previous construction at 105 neurons. We are able to improve this result and to show that an SNP system with 83 neurons having homogenous rules and working in the max sequential manner is universal. Several related results with respect to max-pseudo sequentiality mode are also obtained: 83 neurons are necessary for this case, too. When considering the case of systems without weighted synapses, we show that one needs at most 244 homogenous neurons for reaching universality in the max-pseudo sequentiality case. Show more

Keywords: Membrane computing, spiking neural P system, max spike, universal machine

DOI: 10.3233/FI-2014-1097

Citation: Fundamenta Informaticae, vol. 134, no. 1-2, pp. 167-182, 2014

Authors: Xu, Zihan | Cavaliere, Matteo | An, Pei | Vrudhula, Sarma | Cao, Yu

Article Type: Research Article

Abstract: Spiking neural P systems (in short, SN P systems) have been introduced as computing devices inspired by the structure and functioning of neural cells. The presence of unreliable components in SN P systems can be considered in many different aspects. In this paper we focus on two types of unreliability: the stochastic delays of the spiking rules and the stochastic loss of spikes. We propose the implementation of elementary SN P systems with DRAM-based CMOS circuits that are able to cope with these two forms of unreliability in an efficient way. The constructed bio-inspired circuits can be used to encode …basic arithmetic modules. Show more

DOI: 10.3233/FI-2014-1098

Citation: Fundamenta Informaticae, vol. 134, no. 1-2, pp. 183-200, 2014

Authors: Zhang, Xingyi | Zeng, Xiangxiaing | Pan, Linqiang

Article Type: Research Article

Abstract: Spiking neural P systems (SN P systems, for short) with rules on synapses are a new variant of SN P systems, where the spiking and forgetting rules are placed on synapses instead of in neurons. Recent studies illustrated that this variant of SN P systems is universal working in the way that the synapses starting from the same neuron work in parallel (i.e., all synapses starting from the same neuron should apply their rules if they have rules to be applied). In this work, we consider SN P systems with rules on synapses working in another way: the synapses starting …from the same neuron are restricted to work in a sequential way (i.e., at each step at most one synapse starting from the same neuron applies its rule). It is proved that the computational power of SN P systems with rules on synapses working in this way is reduced; specifically, they can only generate finite sets of numbers. Such SN P systems with rules on synapses are proved to be universal, if synapses are allowed to have weight at most 2 (if a rule which can generate n spikes is applied on a synapse with weight k, then the neuron linking to this synapse will receive totally nk spikes). Two small universal SN P systems with rules on synapses for computing functions are also constructed: a universal system with 26 neurons when using extended rules and each synapse having weight at most 2, and a universal system with 26 neurons when using standard rules and each synapse having weight at most 12. These results illustrate that the weight is an important feature for the computational power of SN P systems. Show more

Keywords: Membrane computing, spiking neural P system, rule on synapse

DOI: 10.3233/FI-2014-1099

Citation: Fundamenta Informaticae, vol. 134, no. 1-2, pp. 201-218, 2014