双稳态神经元模块的分叉与稳定性分析
Bifurcation and Stability Analysis of Bistable Neuromodules
摘要：
本文提出了一个简单的神经模块显示折叠分叉（导致滞后），翻转分叉（周期加倍和解耦的混沌和从）和Neimark-Sacker分叉（准周期和周期分叉）的稳定性分析。第一次，分岔图绘制使用反馈机制。它表明，稳定性曲线和分岔图必须同时处理，以充分了解所涉及的系统的动态。突触权重，偏差和梯度的传递函数是不同的，系统被证明是历史相关的。这项工作可以应用于人工神经网络和开发大脑，并给出了一个非常重要的概括以前的工作在这一领域。
英文摘要：
This paper presents a stability analysis of simple neuromodules displaying fold bifurcations (leading to hysteresis), flip bifurcations (period doubling and undoubling to and from chaos) and Neimark-Sacker bifurcations (quasiperiodic and periodic bifurcations). For the first time, bifurcation diagrams are plotted using a feedback mechanism. It is shown that the stability curves and bifurcation diagrams must be dealt with simultaneously in order to fully understand the dynamics of the systems involved. Synaptic weights, biases and gradients of transfer functions are varied and the system is shown to be history dependent. The work can be applied to artificial neural networks and developing brains and gives a very important generalization of previous work in this field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
