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计算机工程 ›› 2010, Vol. 36 ›› Issue (12): 138-140. doi: 10.3969/j.issn.1000-3428.2010.12.047

• 网络与通信 • 上一篇    下一篇

基于Haar小波的自适应数据压缩方法

罗文华1,王继良1,2   

  1. (1. 长沙环境保护职业技术学院信息技术系,长沙 410004;2. 湖南大学计算机与通信学院,长沙 410082)
  • 出版日期:2010-06-20 发布日期:2010-06-20
  • 作者简介:罗文华(1959-),男,副教授,主研方向:数据压缩, 无线传感器网络;王继良,讲师、硕士
  • 基金资助:
    湖南省自然科学基金资助项目(09JJ3123)

Self-adaptive Data Compression Method Based on Haar Wavelet

LUO Wen-hua1, WANG Ji-liang1,2   

  1. (1. Department of Information Technology, Changsha Environmental Protection College, Changsha 410004;2. School of Computer and Communication, Hunan University, Changsha 410082)
  • Online:2010-06-20 Published:2010-06-20

摘要: 在无线传感器网络中,传感器节点的通信带宽有限,节点输出数据量需要与之匹配。针对该问题,设计高频系数选择算法确定待传输的Haar小波系数选择、量化和编码,通过自适应调整数据压缩率控制输出数据量。理论分析与仿真结果表明,该方法可充分利用节点通信带宽,当温度和湿度数据压缩率为0.9时,数据重构均方差小于0.1。

关键词: 无线传感器网, Haar小波, 数据压缩, 高频系数选择

Abstract: In Wireless Sensor Network(WSN), sensor node has limited communication bandwidth and the mount of node output data need match to it. Aiming at this problem, this paper designs a High frequency Coefficient Selection(HCS) algorithm to ensure Haar wavelet coefficient selection, quantizing and coding for transmitting, and self-adaptively adjusts the compression ratio to control the mount of output data. Theory analysis and simulation results show that this method can make fully use of communication bandwidth, and the Mean Square Error(MSE) of data reconfiguration is less than 0.1 when compression ratio of temperature and humid data is 0.9.

Key words: Wireless Sensor Network(WSN), Haar wavelet, data compression, High frequency Coefficient Selection(HCS)

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