强度驱动信号转导通道的线性噪声近似
Linear Noise Approximation of Intensity-Driven Signal Transduction Channels
摘要：
生化信号转导，一种形式的分子通信，可以使用图形马尔可夫通道与输入调制的过渡率建模。这样的信道模型是强非高斯的。在本文中，我们使用线性噪声近似来构建一类新的高斯加性白噪声通道，捕获完全和部分观察到的强度驱动的信号转导的基本特征。当对输入信号敏感的信道状态转换是直接可观察的时，高频信息比低频信息更有效地转换，并且每带宽的互信息率（频谱效率）显著大于敏感转换和可观察转换不相交时的互信息率。当可观察到的和隐藏的转换都是输入敏感的，我们观察到超加性增加频谱效率。
英文摘要：
Biochemical signal transduction, a form of molecular communication, can be modeled using graphical Markov channels with input-modulated transition rates. Such channel models are strongly non-Gaussian. In this paper we use a linear noise approximation to construct a novel class of Gaussian additive white noise channels that capture essential features of fully- and partially-observed intensity-driven signal transduction. When channel state transitions that are sensitive to the input signal are directly observable, high-frequency information is transduced more efficiently than low-frequency information, and the mutual information rate per bandwidth (spectral efficiency) is significantly greater than when sensitive transitions and observable transitions are disjoint. When both observable and hidden transitions are input-sensitive, we observe a superadditive increase in spectral efficiency.
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