Resumen de Redefined observability matrix for Boolean networks and distinguishable partitions of state space

Yuqian Guo, Weihua Gui, Chunhua Yang

• This paper redefines the observability matrix and defines the observability index for Boolean networks (BNs). In the new definition, a BN is observable if and only if the observability matrix is of full rank. The observability matrix is calculated by a simple algorithm and is applied to the problem of distinguishability of partitions. A partition of the state space is said to be distinguishable if any two distinct subsets are distinguishable, and the finest distinguishable partition (FDP) is finer than any other distinguishable partition. A necessary and sufficient condition is proposed for checking the distinguishability of any given partition, and an algorithm is proposed for calculating the FDP. The proposed results are illustrated by examples.