Noise-tuning-based hysteretic noisy chaotic neural network for data association in multi-target tracking

摘要

With the help of the noise tuning factor, the noise-tuning-based hysteretic noisy chaotic neural network (NHNCNN) can effectively improve the performance of solutions. In order to improve the accuracy of multi-target tracking, we applied the NHNCNN to calculate the joint association probability of data association in multi-target tracking. Compared to the noisy chaotic neural network (NCNN), the HNCNN is more beneficial to solve the problem of data association. The simulation results indicate that the HNCNN is more effective to improve the accuracy of multi-target tracking.