计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
10期
78-81,151
,共5页
压缩感知%无线传感器网络%分布式压缩感知%随机投影%分布式数据压缩
壓縮感知%無線傳感器網絡%分佈式壓縮感知%隨機投影%分佈式數據壓縮
압축감지%무선전감기망락%분포식압축감지%수궤투영%분포식수거압축
compressed sensing%Wireless Sensor Networks%distributed compressed sensing%random project%distributed data compression
无线传感器网络（Wireless Sensor Networks，WSN）负责感知、采集、处理和监控环境数据，但是容易受限于资源。压缩感知（Compressed Sensing，CS）理论表明，利用最优化理论，稀疏信号可以从少量的非自适应线性投影中高概率精确恢复。根据CS理论设计WSN的数据压缩方法只依赖于信号内在的结构和内容，而不是信号的带宽，弥补了WSN的不足；提出了基于稀疏随机投影的编码方法；仿真结果表明系统在满足误差要求条件下构造的数据包减少至结点数目的30%，提高了WSN通信效率，降低了系统能耗。
無線傳感器網絡（Wireless Sensor Networks，WSN）負責感知、採集、處理和鑑控環境數據，但是容易受限于資源。壓縮感知（Compressed Sensing，CS）理論錶明，利用最優化理論，稀疏信號可以從少量的非自適應線性投影中高概率精確恢複。根據CS理論設計WSN的數據壓縮方法隻依賴于信號內在的結構和內容，而不是信號的帶寬，瀰補瞭WSN的不足；提齣瞭基于稀疏隨機投影的編碼方法；倣真結果錶明繫統在滿足誤差要求條件下構造的數據包減少至結點數目的30%，提高瞭WSN通信效率，降低瞭繫統能耗。
무선전감기망락（Wireless Sensor Networks，WSN）부책감지、채집、처리화감공배경수거，단시용역수한우자원。압축감지（Compressed Sensing，CS）이론표명，이용최우화이론，희소신호가이종소량적비자괄응선성투영중고개솔정학회복。근거CS이론설계WSN적수거압축방법지의뢰우신호내재적결구화내용，이불시신호적대관，미보료WSN적불족；제출료기우희소수궤투영적편마방법；방진결과표명계통재만족오차요구조건하구조적수거포감소지결점수목적30%，제고료WSN통신효솔，강저료계통능모。
Wireless Sensor Networks(WSN)are responsible for sensing, collecting, processing and monitoring environ-mental data, but resource is easily limited. The newly emerging Compressed Sensing(CS)theory holds that sparse signals can be exactly reconstructed with high probability from a small amount of non-adaptive linear measurement through opti-mization. A data compression method which is dependent only on the structure and content of the signal, rather than the bandwidth of the signal is designed by sparse random projections through network coding. The results of simulation show that this system not only improves the efficiency of WSN communication by reducing packets to 30% number of nodes, but also reduces the system energy consumption under the error requirement.
