Two Novel Error Models for Power Evolution in Social Opinion Networks with Improved Bounds on Open Attitudes of Agents

This paper proposes two novel error models for power evolution in social opinion network dynamics with stubborn agents. One is formulated to improve the required bound related to stubborn coefficients of agents. Another one uses an approximated equilibrium point to guarantee exponential convergence where a less conservative bound is found based on a numerical method. Examples and simulations are presented to verify the effectiveness of the proposed method.