Neural networks are developed to model the behavior of the brain. One crucial question in
this field pertains to when and how a neural network can memorize a given set of patterns …

State flipping is an effective control method that has just recently been proposed. In this
paper, the state-flipped mechanism is introduced to implement the complete synchronization …

Output stabilizing control of biological systems is of utmost importance in systems biology
since key phenotypes of biological networks are often encoded by a small subset of their …

In this paper, set stability of Boolean networks (BNs) is studied based on semi-tensor
product of matrices. First, an index-vector is introduced to verify whether a BN can be set …

In this paper, we study a stabilization method for probabilistic Boolean networks (PBNs)
using Q-learning, which is one of the typical methods in reinforcement learning. A PBN is a …

We investigate the optimal preview control problem of Boolean Networks (BNs) in this paper.
An augmented system, which can control BNs with a minimal cost function, is established …

In this work, we provide a procedure that allows us to transform certain kinds of deterministic
Boolean networks on minterm or maxterm functions into symmetric ones, so inferring that …

For delayed generalized asynchronous Boolean networks with random disturbances, it is
still uncertain about their robust controllability. This paper uses the semi-tensor product to …

In this paper, a new method of identifying pinned nodes by model-free reinforcement
learning is proposed. With the form of graph, the information of attractors and basins of the …