现代电子技术
現代電子技術
현대전자기술
Modern Electronics Technique
2015年
22期
105-107
,共3页
大型云计算网络%疑似危险信号%检测系统%记忆模块
大型雲計算網絡%疑似危險信號%檢測繫統%記憶模塊
대형운계산망락%의사위험신호%검측계통%기억모괴
large cloud computing network%suspected danger signal%detection system%memory module
传统大型云计算网络下疑似危险信号检测系统对任何一个疑似危险信号均产生报警,系统通常被海量的报警行为干扰,影响了真正的危险信号的检测,导致检测结果不准确的问题.设计并研发了一种引入二进制分段近似匹配方法的大型云计算网络下危险信号检测系统,给出了大型云计算网络下疑似危险信号检测系统的详细结构,通过实时将疑似危险信号检测模块检测到的信号和记忆模块中危险信号库的信号进行匹配,确定信号是否为疑似危险信号.采用记忆模块给出若干危险信号库,用于疑似危险信号的匹配.利用自适应模块发出报警信号和给出该疑似危险信号的特征信息,通过该特征数据对实时疑似危险信号检测模块进行调整.仿真实验结果表明,所设计的系统具有很高的检测精度和适应能力.
傳統大型雲計算網絡下疑似危險信號檢測繫統對任何一箇疑似危險信號均產生報警,繫統通常被海量的報警行為榦擾,影響瞭真正的危險信號的檢測,導緻檢測結果不準確的問題.設計併研髮瞭一種引入二進製分段近似匹配方法的大型雲計算網絡下危險信號檢測繫統,給齣瞭大型雲計算網絡下疑似危險信號檢測繫統的詳細結構,通過實時將疑似危險信號檢測模塊檢測到的信號和記憶模塊中危險信號庫的信號進行匹配,確定信號是否為疑似危險信號.採用記憶模塊給齣若榦危險信號庫,用于疑似危險信號的匹配.利用自適應模塊髮齣報警信號和給齣該疑似危險信號的特徵信息,通過該特徵數據對實時疑似危險信號檢測模塊進行調整.倣真實驗結果錶明,所設計的繫統具有很高的檢測精度和適應能力.
전통대형운계산망락하의사위험신호검측계통대임하일개의사위험신호균산생보경,계통통상피해량적보경행위간우,영향료진정적위험신호적검측,도치검측결과불준학적문제.설계병연발료일충인입이진제분단근사필배방법적대형운계산망락하위험신호검측계통,급출료대형운계산망락하의사위험신호검측계통적상세결구,통과실시장의사위험신호검측모괴검측도적신호화기억모괴중위험신호고적신호진행필배,학정신호시부위의사위험신호.채용기억모괴급출약간위험신호고,용우의사위험신호적필배.이용자괄응모괴발출보경신호화급출해의사위험신호적특정신식,통과해특정수거대실시의사위험신호검측모괴진행조정.방진실험결과표명,소설계적계통구유흔고적검측정도화괄응능력.
The traditional detection system for suspected danger signal in the large cloud computing network gives an alarm to any suspected danger signal. The system is usually disturbed by the huge amounts of alarm actions,which affects on the de-tection of the true danger signal,and leads to the inaccurate detection results. The detection system for danger signal in large cloud computing networks was designed and developed,into which the segmentation approximate matching method of binary is introduced. The detailed structure of the detection system for suspected danger signal in large cloud computing network is of-fered. The signal detected by the suspected danger signal detection module is matched with the signal in danger signal library of the memory module in real time to determine whether the signal is the suspected danger signal. The alarm signal and the feature information of the suspected danger signal are emitted by the adaptive module. The real-time detection module for suspected dan-ger signal is adjusted according to the feature data. The simulation experimental results show that the designed system has high detection precision and adaptability.