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Study on Weak Signal Perception of Optical Communication Network System Based on Double Sparse Dictionary Model

机译:基于双稀疏字典模型的光通信网络系统微弱信号感知研究

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摘要

The traditional weak signal sensing method for optical communication network system has the problem of large sensing error. Therefore, a weak signal sensing method for optical communication network system based on double sparse dictionary model is proposed. The general frame of weak signal sensing method for optical communication network system based on double sparse dictionary model is built. According to the overall framework, a double-sparse dictionary model is established to train the sample weak signals and realize the sparse coding and dictionary update of the weak signals. Orthogonal matching tracking algorithm is used to realize sparse reconstruction of weak signals and accurate perception of weak signals in optical communication networks. Compared with the traditional method, the experimental results show that the proposed method has less error, can more accurately perceive the weak signal of optical communication network system, and has strong practicability.
机译:用于光通信网络系统的传统的弱信号感测方法具有较大的感测误差的问题。因此,提出了一种基于双稀疏字典模型的光通信网络系统弱信号检测方法。建立了基于双稀疏字典模型的光通信网络系统弱信号检测方法的总体框架。根据总体框架,建立了双稀疏字典模型,对样本的弱信号进行训练,实现了对稀疏信号的稀疏编码和字典更新。正交匹配跟踪算法用于在光通信网络中实现弱信号的稀疏重构和对弱信号的准确感知。实验结果表明,与传统方法相比,该方法误差小,可以更准确地感知光通信网络系统的弱信号,具有较强的实用性。

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