Spiking Neural P Systems with Weighted Synapses

Authors:
Linqiang Pan;Xiangxiang Zeng;Xingyi Zhang;Yun Jiang
Affiliations:
Department of Control Science and Engineering, Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Control Science and Engineering, Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, China 430074;Key Laboratory of Intelligent Computing and Signal Processing, School of Computer Science and Technology, Anhui University, Hefei, China 230039;Department of Control Science and Engineering, Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, China 430074
Venue:
Neural Processing Letters
Year:
2012

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Abstract

Spiking neural P systems are a class of distributed parallel computing models inspired from the way neurons communicate with each other by means of electrical impulses, where there is a synapse between each pair of connected neurons. However, in a biological system, there can be several synapses for each pair of connected neurons. In this study, inspired by this biological observation, synapses in a spiking neural P system are endowed with integer weight denoting the number of synapses for each pair of connected neurons. With the price of weight on synapses, quite small universal spiking neural P systems can be constructed. Specifically, a universal spiking neural P system with standard rules and weight having 38 neurons is produced as device of computing functions; as generator of sets of numbers, we find a universal system with standard rules and weight having 36 neurons.