Sequential Coupled Neural P Systems
Zeqiong Lv, Jiangheng Kou, Wenmei Yi, Hong Peng, Xioxiao Song and Jun Wang
Coupled neural P (CNP) systems are a kind of distributed and parallel computing systems abstracted from Eckhorn’s neural model. A CNP system contains several coupled neurons, each with three modules: a receptive field, modulation module, and output module. The computational completeness of CNP systems has been investigated. CNP systems are a kind of synchronous system, and a global clock is assumed to synchronize all neurons. However, this assumption is biologically unrealistic. In this paper, we discuss CNP systems working in sequential mode, i.e., sequential CNP (SCNP) systems. Based on the number of spikes of active neurons and the rule-application strategy, four sequentiality strategies are considered. It is proven that SCNP systems working in these four strategies are Turing universal number-generating/accepting devices. Moreover, two small universal SCNP systems for computing functions working in the max-sequentiality strategy or min-sequentiality strategy are established.
Keywords: Neural-like P system, coupled neural P system, sequential mode, computational completeness