基于人工蜂群算法的超声回波参数估计

将适用于求解组合优化问题和连续优化问题的人工蜂群算法运用于超声回波的非线性高斯模型，提出了一种基于人工蜂群算法的超声回波参数估计新方法，给出了算法的基本步骤，并在不同初始条件下对算法的性能进行了仿真。仿真结果表明，该算法的估计精度与初始值的选择无关，不仅能成功估计出超声回波模型的各个参数，而且可在全局范围内取得最优解，与超声回波参数估计的蚂蚁算法相比，该算法具有收敛速度快，运行时间短，鲁棒性好，可进行实时处理的优点。

Artificial bee colony algorithm for parameter estimation of ultrasonic echo

This paper proposes a parameter estimation method for nonlinear Gaussian model of ultrasonic echo based on artificial bee colony algorithm, which is applied to solve combinatorial optimization problems and continuous optimization problems. It gives the basic steps of the algorithm, and simulates the performance of the algorithm in different initial conditions. Simulation results show that, the estimation accuracy of the algorithm is independent of the initial value selection. And it not only can successfully estimate the various parameters of the ultrasonic echo, but also can achieve the optimal solution in the global scope. Compared with ant colony optimization that applied to ultrasonic echo parameter estimation, the algorithm has the advantages of fast convergence speed, short running time, robustness, real-time processing.