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基于擴(kuò)散算子的帶限圖信號加權(quán)重建策略

楊立山,  游康勇,  郭文彬

楊立山, 游康勇, 郭文彬. 基于擴(kuò)散算子的帶限圖信號加權(quán)重建策略[J]. 電子與信息學(xué)報, 2017, 39(12): 2937-2944. doi: 10.11999/JEIT170106
引用本文: 楊立山, 游康勇, 郭文彬. 基于擴(kuò)散算子的帶限圖信號加權(quán)重建策略[J]. 電子與信息學(xué)報, 2017, 39(12): 2937-2944. doi: 10.11999/JEIT170106
YANG Lishan, YOU Kangyong, GUO Wenbin. Graph Diffusion Operator Based Weighted Reconstruction Strategy for Band-limited Graph Signals[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2937-2944. doi: 10.11999/JEIT170106
Citation: YANG Lishan, YOU Kangyong, GUO Wenbin. Graph Diffusion Operator Based Weighted Reconstruction Strategy for Band-limited Graph Signals[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2937-2944. doi: 10.11999/JEIT170106

基于擴(kuò)散算子的帶限圖信號加權(quán)重建策略

doi: 10.11999/JEIT170106
基金項目: 

國家自然科學(xué)基金(61271181)

Graph Diffusion Operator Based Weighted Reconstruction Strategy for Band-limited Graph Signals

Funds: 

The National Natural Science Foundation of China (61271181)

  • 摘要: 圖信號處理技術(shù)將經(jīng)典信號處理的概念和算法延展到圖結(jié)構(gòu)信號的處理領(lǐng)域。對于帶限圖信號，可以通過分析信號之間的關(guān)聯(lián)性，重建出未采樣的信號。該文分析了未采樣信號的構(gòu)成架構(gòu)，提出一個基于擴(kuò)散算子的未采樣信號迭代重建算法。在每次迭代過程中，將已采樣信號的重建殘差擴(kuò)散至所有未采樣的信號節(jié)點(diǎn)，并進(jìn)一步通過初步估計結(jié)果與重建殘差的加權(quán)處理，提升算法的收斂速度。采用合成數(shù)據(jù)和真實(shí)數(shù)據(jù)進(jìn)行仿真驗(yàn)證，實(shí)驗(yàn)結(jié)果顯示所提出的算法具有低重建誤差和快速收斂的特點(diǎn)。
    Abstract: Signal processing on graphs extends signal processing concepts and methodologies from the classical signal processing theory to data indexed by general graphs. For a band-limited graph signal, the unsampled data can be reconstructed from the sampled data by exploiting the relationship of the graph signals. This paper proposes a concept of graph diffusion operator for signal processing on graphs, and uses the operator to reconstruct band-limited graph signals from the sampled data. In each iteration, the residuals of the sampled vertices are propagated to all the unsampled vertices, and the known information and initial estimated results are further exploited via weighted process, aiming at accelerating the convergence. An analysis framework is proposed for the unsampled graph signals. The simulation results of synthetic data and real-world data demonstrate the wonderful effectiveness of the proposed reconstruction strategy.
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  • 文章訪問數(shù):  1083
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  • 被引次數(shù): 0
出版歷程
  • 收稿日期:  2017-02-08
  • 修回日期:  2017-09-11
  • 刊出日期:  2017-12-19

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