Homogeneous spiking neural P systems with structural plasticity

被引:0
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作者
Ren Tristan A. de la Cruz
Francis George C. Cabarle
Ivan Cedric H. Macababayao
Henry N. Adorna
Xiangxiang Zeng
机构
[1] University of the Philippines - Diliman,Department of Computer Science, Algorithms and Complexity Laboratory
[2] Hunan University,School of Information Science and Engineering
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关键词
Membrane computing; Spiking neural P systems; Homogeneous neurons; Structural plasticity;
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摘要
Spiking neural P system (SNP system) is a model of computation inspired by the mechanism of spiking neurons. An SNP system is a directed graph of neurons that can communicate with each other using an object known as a spike (the object spike represents action potential or nerve impulse). Spiking neural P systems with structural plasticity (SNPSP system) is a variant of the SNP system model. It incorporates the concept of structural plasticity to the SNP system model. SNPSP systems have the ability to add and delete connections between neurons. In SNPSP systems, the behavior of a neuron can be “programmed” by giving it a set of rules. Different set of rules will result in different behaviors. In this work, we show that it is possible to construct a universal SNPSP system where all the neurons in the system use the same set of rules. Such systems are called homogeneous SNPSP systems.
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页码:10 / 21
页数:11
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