基于免疫网络的异态电磁信号监测模型

针对人工免疫系统运用于信号密度适中的日常异态信号监测时，系统对检测器数量要求过高的问题，本文对现有的模型进行了改进，提出了基于免疫网络的异态电磁信号监测模型。模型引入数据正向压缩和检测器相互抑制的机制，使得系统对检测器数量的要求明显降低。本文采用实际无线电监测数据对模型进行了检验，并与基于阴性选择的模型进行对比，验证了该模型在信号密度适中的日常监测中可大幅减少对检测器数量的要求，提高了监测效率。

Anomalistic electromagnetism signal detection model based on immune network

When Artificial Immune System (AIS) is used in the daily anomalistic electromagnetism signal detection at the moderate signal density issue, there exists redundancy in the detectors of system, an anomalistic electromagnetism signal detection model based on immune network is presented in this paper. By introducing the notions of data compression and detector suppression, the model can decrease the number of detectors efficiently. The model has been tested by real wireless signal monitoring data, and its results are compared to the model based on negative selection theory, which indicates that the proposed model can reduce the number of detectors and decrease the detection time apparently.