论文部分内容阅读
本文通过对联合概率数据关联的性能特征的分析,将其归结为一类约束组合优化问题,在此基础上,利用Hopfield神经网络求解典型的约束组合优化问题(旅行推销员问题)的方法,解决了传统的联合概率数据关联中出现的计算量组合爆炸现象,仿真结果表明,该方法效果良好,在密集多回波环境下,其优越性能更为突出。
Based on the analysis of performance characteristics associated with joint probabilistic data, this paper concludes a class of constrained combinatorial optimization problems. Based on this, this paper uses Hopfield neural network to solve the typical constrained combinatorial optimization problem (travel salesman problem) The combinatorial explosion phenomenon appeared in the traditional joint probability data association. The simulation results show that the proposed method is effective and has the outstanding performance under dense multi-echo environment.