Asynchronous Spiking Neural P Systems: Decidability and Undecidability
Asynchronous Spiking Neural P Systems: Decidability and Undecidability
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DOI：
10.1007/978-3-540-77962-9_26
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发表时间：
2007-06
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影响因子：
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通讯作者：
M. Cavaliere;Ö. Eğecioğlu;O. Ibarra;M. Ionescu;G. Paun;Sara Woodworth
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文献类型：
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作者：
M. Cavaliere;Ö. Eğecioğlu;O. Ibarra;M. Ionescu;G. Paun;Sara Woodworth
在寻找“现实的”仿生计算模型时，我们考虑异步尖峰神经 P 系统，希望获得一类具有可判定属性的计算设备。然而，尽管众所周知非同步会降低计算能力，但在使用扩展规则（规则可以产生多个尖峰）的情况下，我们再次获得与图灵机的等价性（解释为数字向量集的生成器）。对于受限尖峰神经 P 系统的情况，该问题仍然存在，该系统的规则只能产生一个尖峰。另一方面，我们证明异步尖峰神经 P 系统，具有特定的停止方式，使用扩展规则，并且每个神经元要么是有界的，要么是无界的，相当于部分盲计数器机器，因此具有许多可判定的属性。
In search for “realistic” bio-inspired computing models, we consider asynchronous spiking neural P systems, in the hope to get a class of computing devices with decidable properties. However, although the non-synchronization is known in general to decrease the computing power, in the case of using extended rules (several spikes can be produced by a rule) we obtain again the equivalence with Turing machines (interpreted as generators of sets of vectors of numbers). The problem remains open for the case of restricted spiking neural P systems, whose rules can only produce one spike. On the other hand, we prove that asynchronous spiking neural P systems, with a specific way of halting, using extended rules and where each neuron is either bounded or unbounded, are equivalent to partially blind counter machines and, therefore, have many decidable properties.