Spiking Neural P Systems with Neuron Division

Spiking Neural P Systems with Neuron Division
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具有神经元分裂的尖峰神经 P 系统

DOI:
10.1007/978-3-642-18123-8_28
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发表时间:
2010-08
期刊:
Lecture Notes in Computer Science . Springer Berlin/Heidelberg
影响因子:
--
通讯作者:
Linqiang Pan
Linqiang Pan
中科院分区:
其他
文献类型:
--
作者:
Jun Wang;Hendrik Jan Hoogeboom;Linqiang Pan

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Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. The features of neuron division and neuron budding are recently introduced into the framework of SN P systems, and it was shown that SN P systems with neuron division and neuron budding can efficiently solve computationally hard problems. In this work, the computation power of SN P systems with neuron division only, without budding, is investigated; it is proved that a uniform family of SN P systems with neuron division can efficiently solve SAT in a deterministic way, not using budding, while additionally limiting the initial size of the system to a constant number of neurons. This answers an open problem formulated by Pan et al.
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