Journal ArticleDOI
Weighted Fuzzy Spiking Neural P Systems
TLDR
A weighted fuzzy backward reasoning algorithm, based on WFSN P systems, is developed, which can accomplish dynamic fuzzy reasoning of a rule-based system more flexibly and intelligently.Abstract:
Spiking neural P systems (SN P systems) are a new class of computing models inspired by the neurophysiological behavior of biological spiking neurons. In order to make SN P systems capable of representing and processing fuzzy and uncertain knowledge, we propose a new class of spiking neural P systems in this paper called weighted fuzzy spiking neural P systems (WFSN P systems). New elements, including fuzzy truth value, certain factor, weighted fuzzy logic, output weight, threshold, new firing rule, and two types of neurons, are added to the original definition of SN P systems. This allows WFSN P systems to adequately characterize the features of weighted fuzzy production rules in a fuzzy rule-based system. Furthermore, a weighted fuzzy backward reasoning algorithm, based on WFSN P systems, is developed, which can accomplish dynamic fuzzy reasoning of a rule-based system more flexibly and intelligently. In addition, we compare the proposed WFSN P systems with other knowledge representation methods, such as fuzzy production rule, conceptual graph, and Petri nets, to demonstrate the features and advantages of the proposed techniques.read more
Citations
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Journal ArticleDOI
Fault Diagnosis of Electric Power Systems Based on Fuzzy Reasoning Spiking Neural P Systems
TL;DR: The results of case studies show that FDSNP is effective in diagnosing faults in power transmission networks for single and multiple fault situations with/without incomplete and uncertain SCADA data, and is superior to four methods reported in the literature in terms of the correctness of diagnosis results.
Journal ArticleDOI
Spiking Neural P Systems with Communication on Request.
TL;DR: The Spiking Neural Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used.
Journal ArticleDOI
On the Universality of Axon P Systems
TL;DR: It is proved that four nodes are enough for axon P systems to achieve universality as number generators and function computing devices, and it is illustrated that the simple linear structure is enough to achieve a desired computational power.
Journal ArticleDOI
Design of logic gates using spiking neural P systems with homogeneous neurons and astrocytes-like control
TL;DR: A novel method of constructing logic circuits that work in a neural-like manner is demonstrated, as well as shed some lights on potential directions of designing neural circuits theoretically.
Journal ArticleDOI
Spiking neural P systems with request rules
Tao Song,Linqiang Pan +1 more
TL;DR: It is obtained that SN P systems with request rules are Turing universal, even with a small number of neurons, and with 47 neurons such systems can compute any Turing computable function.
References
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