An improved universal spiking neural P system with generalized use of rules

2019 ◽  
Vol 1 (4) ◽  
pp. 270-278 ◽  
Author(s):  
Yun Jiang ◽  
Yansen Su ◽  
Fen Luo
Author(s):  
Francis George Cabarle ◽  
Henry Adorna ◽  
Miguel A. Martínez-del-Amor ◽  
Mario J. Pérez-Jiménez

2006 ◽  
Vol 17 (04) ◽  
pp. 975-1002 ◽  
Author(s):  
GHEORGHE PĂUN ◽  
MARIO J. PÉREZ-JIMÉNEZ ◽  
GRZEGORZ ROZENBERG

We continue here the study of the recently introduced spiking neural P systems, which mimic the way that neurons communicate with each other by means of short electrical impulses, identical in shape (voltage), but emitted at precise moments of time. The sequence of moments when a neuron emits a spike is called the spike train (of this neuron); by designating one neuron as the output neuron of a spiking neural P system II, one obtains a spike train of II. Given a specific way of assigning sets of numbers to spike trains of II, we obtain sets of numbers computed by II. In this way, spiking neural P systems become number computing devices. We consider a number of ways to assign (code) sets of numbers to (by) spike trains, and prove then computational completeness: the computed sets of numbers are exactly Turing computable sets. When the number of spikes present in the system is bounded, a characterization of semilinear sets of numbers is obtained. A number of research problems is also formulated.


2010 ◽  
Vol 52 (11-12) ◽  
pp. 1940-1946 ◽  
Author(s):  
Xiangxiang Zeng ◽  
Chun Lu ◽  
Linqiang Pan

2020 ◽  
Vol 2 (1) ◽  
pp. 42-48 ◽  
Author(s):  
Otgonnaran Ochirbat ◽  
Tseren-Onolt Ishdorj ◽  
Gordon Cichon

2018 ◽  
Vol 13 (4) ◽  
pp. 521-536 ◽  
Author(s):  
Haina Rong ◽  
Mianjun Ge ◽  
Gexiang Zhang ◽  
Ming Zhu

This paper presents a novel approach for detecting fault lines in a small current grounding system using fuzzy reasoning spiking neural P systems. In this approach, six features of current/voltage signals in a small current grounding system are analyzed by considering transient and steady components, respectively; a fault measure is used to quantify the possibility that a line is faulty; information gain degree is discussed to weight the importance of each of the six features; rough set theory is applied to reduce the features; and finally a fuzzy reasoning spiking neural P system is used to construct fault line detection models. Six cases in a small current grounding system prove the effectiveness of the introduced approach.


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