在适应性局部能量平衡下,光温度神经网络中的波传播
Feifei Yang1, Qun Guo1, Guodong Ren2
1College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China.
Journal of biological physics
|July 3, 2024
概括
这项研究引入了一个对温度和光敏感的神经元模型,以探索神经网络中的能量动态. 局部能量平衡和适应性参数调节导致波浪传播的模式形成和梯度能量分布.
科学领域:
- 计算神经科学是一种神经科学.
- 非线性动力学是一种非线性动力学.
- 生物物理学的生物物理.
背景情况:
- 由于固有的灵活性,可刺激的介质在外部刺激下变形.
- 可以模拟神经网络中的信号传播,与与能量积累/释放相关的形状变形.
- 异质性和缺陷源于神经网络中的能量动态.
研究的目的:
- 开发一个对温度和光敏感的神经元模型.
- 研究神经网络中的能量传播和扩散.
- 分析局部能源平衡产生的模式形成.
主要方法:
- 一个非线性电路模型,使用光管和热敏电阻来测量温度与光的灵敏度.
- 对于神经元模型的汉密尔顿能量的理论导出.
- 在带有电突突触的方形阵列上构建一个正规的神经网络.
- 引入噪音干扰以诱导当地能源多样性.
主要成果:
- 获得了神经元模型的汉密尔顿能量函数.
- 在诱导能源多样性后,在网络中观察到能量扩散和扩散.
- 对内在参数的自适应调节降低了当地的能源多样性,促进了模式形成.
- 地方能源平衡被证明会产生异质性和缺陷.
结论:
- 当地能量平衡对于在神经网络中产生异质性和缺陷至关重要.
- 神经元中的适应性参数转移促进了能量平衡和梯度能量分布.
- 开发的模型支持梯度能量分布,用于在可刺激介质中传播波.
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