大规模物联网终端密文数据分段小波降噪算法仿真

doi:10.13229/j.cnki.jdxbgxb.20220748

摘要/Abstract

摘要：

为有效滤除终端密文数据中的噪声，提出一种大规模物联网终端密文数据分段小波降噪算法。采用周期图谱估计特征提取方法提取不同类型数据的连续谱分量和线谱分量，获取密文数据的噪声特征。通过噪声数据在尺度空间的最大投影构建能量匹配准则，采用结构化小波滤波器组建立与信号能量一致的最优能量匹配小波。并通过波形匹配准则，使用优化函数建立与信号波形相同的最优波形匹配小波，完成大规模物联网终端密文数据分段小波降噪处理。经实验测试结果表明：所提算法能有效降低数据降噪延时，同时能获取较满意的降噪效果。

关键词: 大规模物联网, 终端密文数据, 分段, 小波降噪

Abstract:

In order to effectively filter the noise in terminal ciphertext data， a segmentation wavelet noise reduction algorithm for large-scale IoT terminal ciphertext data is proposed. The continuous spectral components and line spectral components of different types of data are extracted by the periodogram estimation feature extraction method， and the noise features of the ciphertext data are obtained. The maximum projection of noise data in the scale space is used to construct the energy matching criterion， and the structured wavelet filter bank is used to establish the optimal energy matching wavelet consistent with the signal energy. Through the waveform matching criterion， the optimal waveform matching wavelet which is the same as the signal waveform is established by using the optimization function to complete the segmented wavelet de-noising of the ciphertext data of the large-scale IOT terminal. The experimental test results show that the proposed algorithm can effectively reduce the delay of data noise reduction， and can also obtain satisfactory noise reduction effect.

Key words: large-scale internet of things, terminal ciphertext data, segmentation, wavelet noise reduction

中图分类号:

TM933

曹守启,孔凡慧,张铮,熊如意. 大规模物联网终端密文数据分段小波降噪算法仿真[J]. 吉林大学学报(工学版), 2023, 53(8): 2358-2363.

Shou-qi CAO,Fan-hui KONG,Zheng ZHANG,Ru-yi XIONG. Simulation of segmentation wavelet noise reduction algorithm for large⁃scale IoT terminal ciphertext data[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(8): 2358-2363.

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测试组次	降噪时延/ms
测试组次	本文算法	文献［3］算法	文献［4］算法
1	0.254	0.264	0.271
2	0.283	0.299	0.300
3	0.301	0.315	0.334
4	0.326	0.334	0.359
5	0.345	0.358	0.376
6	0.366	0.370	0.389