<?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%">Alberto Leporati</style></author><author><style face="normal" font="default" size="100%">Giancarlo Mauri</style></author><author><style face="normal" font="default" size="100%">Claudio Zandron</style></author><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></authors></contributors><titles><title><style face="normal" font="default" size="100%">Uniform solutions to SAT and Subset Sum by spiking neural P systems</style></title><secondary-title><style face="normal" font="default" size="100%">Natural Computing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Membrane computing; Spiking neural P system; SAT problem; Subset sum problem; Complexity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/s11047-008-9091-y</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Amsterdam, Netherlands</style></pub-location><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">681-702</style></pages><abstract><style face="normal" font="default" size="100%">We continue the investigations concerning the possibility of using spiking neural P systems as a framework for solving computationally hard problems, addressing two problems which were already recently considered in this respect: SubsetSum and SAT. For both of them we provide uniform constructions of standard spiking neural P systems (i.e., not using extended rules or parallel use of rules) which solve these problems in a constant number of steps, working in a non-deterministic way. This improves known results of this type where the construction was non-uniform, and/or was using various ingredients added to the initial definition of spiking neural P systems (the SN P systems as defined initially are called here “standard”). However, in the SubsetSum case, a price to pay for this improvement is that the solution is obtained either in a time which depends on the value of the numbers involved in the problem, or by using a system whose size depends on the same values, or again by using complicated regular expressions. A uniform solution to SAT is also provided, that works in constant time. </style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record></records></xml>