Cheng Daizhan, Qi Hongsheng
Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China.
IEEE Trans Neural Netw. 2010 Apr;21(4):584-94. doi: 10.1109/TNN.2009.2039802. Epub 2010 Feb 17.
This paper provides a comprehensive framework for the state-space approach to Boolean networks. First, it surveys the authors' recent work on the topic: Using semitensor product of matrices and the matrix expression of logic, the logical dynamic equations of Boolean (control) networks can be converted into standard discrete-time dynamics. To use the state-space approach, the state space and its subspaces of a Boolean network have been carefully defined. The basis of a subspace has been constructed. Particularly, the regular subspace, Y-friendly subspace, and invariant subspace are precisely defined, and the verifying algorithms are presented. As an application, the indistinct rolling gear structure of a Boolean network is revealed.
本文为布尔网络的状态空间方法提供了一个全面的框架。首先,综述了作者近期在该主题上的工作:利用矩阵的半张量积和逻辑的矩阵表示,布尔(控制)网络的逻辑动态方程可转化为标准离散时间动态方程。为了使用状态空间方法,已仔细定义了布尔网络的状态空间及其子空间。构建了子空间的基。特别地,精确地定义了正则子空间、Y友好子空间和不变子空间,并给出了验证算法。作为一个应用,揭示了布尔网络的模糊滚动齿轮结构。