Introduction to algorithms
Journal of Computer and System Sciences
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Membrane Computing: An Introduction
Membrane Computing: An Introduction
A New Class of Symbolic Abstract Neural Nets: Tissue P Systems
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Solving NP-Complete Problems Using P Systems with Active Membranes
UMC '00 Proceedings of the Second International Conference on Unconventional Models of Computation
Fundamenta Informaticae
Normal forms for spiking neural P systems
Theoretical Computer Science
Computing with spiking neural p systems: traces and small universal systems
DNA'06 Proceedings of the 12th international conference on DNA Computing
On the Computational Complexity of Spiking Neural P Systems
UC '08 Proceedings of the 7th international conference on Unconventional Computing
Uniform solutions to SAT and 3-SAT by spiking neural P systems with pre-computed resources
Natural Computing: an international journal
Bibliography of spiking neural P systems
Natural Computing: an international journal
Implementing Sorting Networks with Spiking Neural P Systems
Fundamenta Informaticae
Computational Complexity of Simple P Systems
Fundamenta Informaticae
Solving SUBSET SUM by Spiking Neural P Systems with Pre-computed Resources
Fundamenta Informaticae
Uniform solutions to SAT and Subset Sum by spiking neural P systems
Natural Computing: an international journal
Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources
Theoretical Computer Science
On the computational complexity of spiking neural P systems
Natural Computing: an international journal
Polynomial complexity classes in spiking neural P systems
CMC'10 Proceedings of the 11th international conference on Membrane computing
Spiking neural P systems with neuron division
CMC'10 Proceedings of the 11th international conference on Membrane computing
Computing the maximum bisimulation with spiking neural P systems
Computation, cooperation, and life
Solving NP-Complete problems by spiking neural p systems with budding rules
WMC'09 Proceedings of the 10th international conference on Membrane Computing
Implementing Sorting Networks with Spiking Neural P Systems
Fundamenta Informaticae
Computational Complexity of Simple P Systems
Fundamenta Informaticae
Solving SUBSET SUM by Spiking Neural P Systems with Pre-computed Resources
Fundamenta Informaticae
Solving directed hamilton path problem in parallel by improved SN p system
ICPCA/SWS'12 Proceedings of the 2012 international conference on Pervasive Computing and the Networked World
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Starting from an extended nondeterministic spiking neural P system that solves the Subset SUM problem in a constant number of computation steps, recently proposed in a previous paper, we investigate how different properties of spiking neural P systems affect the capability to solve numerical NP-complete problems. In particular, we show that by using maximal parallelism we can convert any given integer number from the usual binary notation to the unary form, and thus we can initialize the above P system with the required (exponential) number of spikes in polynomial time. On the other hand, we prove that this conversion cannot be performed in polynomial time if the use of maximal parallelism is forbidden. Finally, we show that if we can choose whether each neuron works in the nondeterministic vs. deterministic and/or in the maximal parallel vs. sequential way, then there exists a uniform family of spiking neural P systems that solves the SUBSET SUM problem.