Adaptive affinity propagation algorithm based on new strategy of dynamic damping factor and preference

Abstract

The affinity propagation algorithm has been extensively applied in various fields. However, it is still faces two severe challenges in actual applications: one is that the algorithm may be nonconvergent; and the other is that the convergence speed is low. Aiming at solving these two problems, an adaptive affinity propagation algorithm based on a new strategy of dynamic damping factor and preference is proposed in this paper. On one hand, the dynamic damping factor changes the factor value according to the check state of oscillation to eliminate and escape from the oscillation. On the other hand, dynamic preference adjusts the value of the preference based on the bisection and memory tuple to reduce the search scope of the target preferences continuously. Simulation results show that the proposed algorithms can solve the potential nonconvergence problem effectively and reduce the time consumed significantly. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.