Finite-Time Topology Identification of Multi-weighted Coupled Neural Networks with and without Parameter Uncertainties
Han-Yu Wu · 2021
This paper mainly studies the problem of finite-time topology identification for multi-weighted coupled neural networks with and without parameter uncertainties. By designing the response networks, several parameter adjustment strategies and state feedback controllers, and making use of some inequality techniques, we identify the topology of original networks based on the synchronization property. Finally, an example is given to illustrate the effectiveness of the proposed finite-time topology identification criterion.