<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jun Wang</style></author><author><style face="normal" font="default" size="100%">Hendrik J. Hoogeboom</style></author><author><style face="normal" font="default" size="100%">Linqiang Pan</style></author><author><style face="normal" font="default" size="100%">Gheorghe Paun</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Gheorghe Paun</style></author><author><style face="normal" font="default" size="100%">Mario J. Pérez-Jiménez</style></author><author><style face="normal" font="default" size="100%">Agustín Riscos-Núñez</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Spiking neural P systems with weights and thresholds</style></title><secondary-title><style face="normal" font="default" size="100%">10th Workshop on Membrane Computing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">24-27/08/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.gcn.us.es/?q=procwmc10</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Marpapublicidad</style></publisher><pub-location><style face="normal" font="default" size="100%">Curtea de Arges, Rumania</style></pub-location><pages><style face="normal" font="default" size="100%">514-533</style></pages><abstract><style face="normal" font="default" size="100%">A variant of spiking neural P systems is introduced, with (positive or nega-
tive) weights on synapses and with the restriction that the rules of a neuron fires when
the potential of that neuron equals a given threshold. The involved numbers - weights,
thresholds, potential consumed by each rule - can be real (computable) numbers, ratio-
nal, integer, natural numbers. The power of the obtained systems is investigated. For
instance, it is shown that integer numbers (very restricted: 1;-1 for weights, 1 and 2 for
thresholds and for writing the rules) suffice in order to compute all Turing computable
sets of numbers, both in the generative and the accepting modes. Using only natural
numbers we characterize the family of semilinear sets of numbers. Some open problems
and suggestions for further research are formulated.</style></abstract></record></records></xml>