对改进的菲茨休-林泽尔神经元及其无倍数电路实施的研究
Zeric Njitacke Tabekoueng1, Balakrishnan Sriram2, Karthikeyan Rajagopal2
1Department of Electrical and Electronic Engineering, College of Technology (COT), University of Buea, P.O. Box 63, Buea, Cameroon.
Chaos (Woodbury, N.Y.)
|June 27, 2023
概括
一个改进的FitzHugh-Rinzel神经元模型使用正弦过倍函数来实现无倍数的实现. 这种新的电子神经电路展示了稳定和不稳定的节点,表现出爆发和尖的行为.
科学领域:
- 神经科学是一个神经科学.
- 电子工程 电子工程
- 计算神经科学是一种神经科学.
背景情况:
- 神经元的数学模型对于理解神经动力学和神经形态工程中的应用至关重要.
- 菲茨休-林泽尔模型是神经元刺激性的简化但有效的模型.
- 现有的模型通常涉及复杂的非线性组件,需要大量的计算资源.
研究的目的:
- 引入一个改进的FitzHugh-Rinzel神经元模型,其非线性组成部分没有倍数.
- 分析拟议的神经元模型的稳定性和动态行为.
- 通过电路实现和模拟来验证模型的性能.
主要方法:
- 取代了传统的立方非线性,用正弦的过度波函数来实现使用两个二极管的无倍数实现.
- 分析模型稳定性,确定固定点周围的稳定和不稳定的节点.
- 根据赫尔姆霍尔茨定理推导出汉密尔顿函数来估计能量释放.
- 执行数值模拟来计算动态行为,包括爆破和尖端.
- 使用Pspice模拟的电子神经电路验证了结果.
主要成果:
- 拟议的模型是无倍数的,使用两个二极管有效地实现.
- 该模型展示了稳定和不稳定的节点,表明复杂的动态.
- 数字模拟显示了连贯和不连贯的状态,包括爆裂和尖端活动.
- 通过不同的初始状态观察到两种不同类型的电活动相同的参数.
- 在Pspice中的电路模拟证实了模型的动态行为.
结论:
- 改进的FitzHugh-Rinzel神经元模型为神经形态工程提供了一种高效和验证的方法.
- 没有乘数的设计简化了硬件实现,同时保留了丰富的动态行为.
- 该模型能够表现出多种活动,包括不同类型的同时活动的能力,增强了其对复杂神经模拟的潜力.
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