Based on the antibody clonal selection theory of immunology, the immune clonal selection algorithm ( ICSA) to select the best initial shift register of M-sequences is presented here. 基于免疫学中的抗体克隆选择,提出了用免疫克隆算法(ICSA)来搜索M序列最优初始移位寄存器值。
Simulation results show that the proposed detector not only can achieve the global optimization values in fast convergence rate, but also is superior to the conventional receiver and the multiuser detectors based on the previous optimal algorithms in the cancellation of multiple-access-interference and near-far effect. 仿真结果证明了ICSA检测器能够快速收敛到全局最优解,并且无论抗多址干扰和抗远近效应能力都优于传统方法和一些应用优化算法的多用户检测器。
The simulation results show that ICSA based on this method of mutation can improve the rapidity of learning BP network well and avoid prematurity effectively. 仿真实验表明,基于这种变异方法的免疫克隆选择算法可以很好地提高BP网络的学习速度,有效地避免算法过早收敛的问题。
By introducing the information processing mechanism of artificial immune systems and neural network to CSA, an immune clonal selection algorithm ( ICSA) was proposed. 把人工免疫系统和神经网络系统的信息处理机制引入到CSA提出了免疫克隆选择算法。
An intelligent algorithm called Immune Clone Selection Algorithm ( ICSA) with fast speed and convergence to the best solution is discussed. 免疫克隆选择算法是一种快速且保证收敛到最优的智能搜索算法,把它与最小熵原理结合作为准则来实现二维参数的搜索。
Details are as follows: Firstly, a modified Immune Clonal Selection Algorithm ( ICSA) is proposed. 具体内容如下:首先,提出一种改进的免疫克隆选择算法。