Two Methods of Dealing with Large-Scale Logical Networks

In the past few decades, the computational complexity of logical networks (LNs) has become a heated research topic. This paper aims to reduce the computational complexity of the existing results in order to make them applicable to large-scale LNs. The topological structure of large-scale probabilistic logical networks (PLNs) is analyzed via matrix decomposition technique. By virtue of aggregation method, this paper considers the reachability of large-scale logical control networks (LCNs), and some efficient criteria are established. Finally, some illustrative examples are given to demonstrate the effectiveness of the obtained new results.