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Spiking Neural P Systems with Weighted Synapses

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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.

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Authors and Affiliations

  1. Department of Control Science and Engineering, Key Laboratory of Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China

    Linqiang Pan, Xiangxiang Zeng & Yun Jiang

  2. Key Laboratory of Intelligent Computing and Signal Processing, School of Computer Science and Technology, Anhui University, Hefei, 230039, Anhui, China

    Xingyi Zhang

Authors
  1. Linqiang Pan
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  2. Xiangxiang Zeng
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  3. Xingyi Zhang
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  4. Yun Jiang
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Correspondence to Xiangxiang Zeng.

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Pan, L., Zeng, X., Zhang, X. et al. Spiking Neural P Systems with Weighted Synapses. Neural Process Lett 35, 13–27 (2012). https://doi.org/10.1007/s11063-011-9201-1

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  • DOI: https://doi.org/10.1007/s11063-011-9201-1

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