噪声如何影响线性循环网络的记忆能力
How noise affects memory in linear recurrent networks
- 通过功率谱密度分析噪声对记忆的影响机制
- 特定噪声分布下记忆不受强度影响，即使噪声很强
- 结果在人脑信号中验证，适用于神经科学建模
本文理论研究了噪声对线性循环网络记忆能力的影响。记忆定义为网络瞬时状态对先前输入的存储能力，其受相关或不相关噪声影响。揭示两个核心性质：第一，噪声导致的记忆衰减完全由噪声的功率谱密度（PSD）决定；第二，若功率谱密度属于特定分布类（包括幂律分布），则记忆不会随噪声强度增加而下降。研究结果在人类脑电数据上得到验证，表现出良好一致性。
原文摘要 · Abstract (English)
The effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous state of network, which receives a correlated or uncorrelated noise. Two major properties are revealed: First, the memory reduced by noise is uniquely determined by the noise's power spectral density (PSD). Second, the memory will not decrease regardless of noise intensity if the PSD is in a certain class of distribution (including power law). The results are verified using the human brain signals, showing good agreement.
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