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Pattern Synchronization in a Two-Layer Neuronal Network 被引量:1

Pattern Synchronization in a Two-Layer Neuronal Network
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摘要 Pattern synchronization in a two-layer neuronal network is studied. For a single-layer network of Rulkov map neurons, there are three kinds of patterns induced by noise. Additive noise can induce ordered patterns at some intermediate noise intensities in a resonant way; however, for small and large noise intensities there exist excitable patterns and disordered patterns, respectively. For a neuronal network coupled by two single-layer networks with noise intensity differences between layers, we find that the two-layer network can achieve synchrony as the interlayer coupling strength increases. The synchronous states strongly depend on the interlayer coupling strength and the noise intensity difference between layers. Pattern synchronization in a two-layer neuronal network is studied. For a single-layer network of Rulkov map neurons, there are three kinds of patterns induced by noise. Additive noise can induce ordered patterns at some intermediate noise intensities in a resonant way; however, for small and large noise intensities there exist excitable patterns and disordered patterns, respectively. For a neuronal network coupled by two single-layer networks with noise intensity differences between layers, we find that the two-layer network can achieve synchrony as the interlayer coupling strength increases. The synchronous states strongly depend on the interlayer coupling strength and the noise intensity difference between layers.
出处 《Chinese Physics Letters》 SCIE CAS CSCD 2009年第6期69-72,共4页 中国物理快报(英文版)
基金 Supported by the National Natural Science Foundation of China under Grant No 10872014.
关键词 gamma-ray bursts GAMMA-RAYS RELATIVITY gamma-ray bursts, gamma-rays, relativity
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参考文献11

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