Zhang Yan-xin

Applying Hopfield neural network to QoS routing in communication network

The main goal of routing solutions is to satisfy the requirements of the Quality of Service (QoS) for every admitted connection as well as to achieve a global efficiency in resource utilization. In this paper proposes a solution based on Hopfield neural network (HNN) to deal with one of representative routing problems in uni-cast routing, i. e. the multi-constrained (MC) routing problem. Computer simulation shows that we can obtain the optimal path very rapidly with our new Lyapunov energy functions.

Role of Self-Coupling in Dynamics of Diluted Hopfield Neural Networks

The dynamical equation of diluted Hopfield neural networks with self-couplings is calculated by analytical approach. The presented results show that the self-coupling strongly influences the dynamical behavior of the network, making the critical loading value αc smaller remarkably and the size of basin of attraction decrease.

A cascaded model of neural network for pattern recognition

A cascaded model of neural network and its learning algorithm suitable for optical implementation are proposed. Computer simulations have shown that this model may successfully be applied to an error-tolerance pattern recognitions of multiple 3-D targets with arbitrary spatial orientations.