Abstract: Based on the coincidence characteristics of sensor data, this paper proposes a data compress algorithm based on interval wavelet and coincidence. First to processing the sensor data with the data strong coincidence characteristics, the data with strong coincidence characteristics can be estimated using least-squares method. Uses the interval wavelet which has a good frequency characteristic, the algorithm reduces the transmitted data when communicating in sensor network. Theoretical analysis and simulation results show that the algorithm can effectively compress sensor data and reduce energy consumption greater.

Key words: Wireless Sensor Networks(WSN), interval wavelet, coincidence characteristic, data compression

摘要： 根据传感数据的偶合特征，提出一种基于区间小波的偶合数据压缩算法。根据数据的强偶合特性处理传感数据，利用最小二乘法对强偶合数据进行曲线拟合，结合区间小波良好的分频特性，减少传感器网络中传输的数据量。理论分析和仿真实验结果表明，该算法能对传感数据进行有效压缩，减少网络能耗。

关键词: 无线传感器网络, 区间小波, 偶合特征, 数据压缩

CLC Number: 

• TP393