Abstract: Hardware/software partitioning is one of the most important issues of the design of embedded systems. This paper described an approach based on immune particle swarm optimization algorithm. Affinity, clone copy operator, clone hyper-mutation operator and clone selection operator were redefined. The experimental results show that the algorithm can not only escape from local extreme but also improve the precision of the optimal solution.

Key words: hardware/software, Particle Swarm Optimization (PSO), immune clone, operator

摘要： 针对嵌入式系统软硬件划分问题，提出一种粒子群算法与免疫克隆选择算法相结合的免疫粒子群软硬件划分方法。该算法重新定义了亲和力、克隆算子、变异算子和选择算子，有效克服了粒子群算法容易陷入局部最优的缺点。仿真实验表明该算法有效提高了解的精度，获得了更合理的软硬件划分结果。

关键词: 软硬件, 粒子群优化算法, 免疫克隆, 算子