Pulse signal recovery is to extract useful amplitude and time information from the pulse signal contaminated by noise. It is a great challenge to precisely recover the pulse signal in loud background noise. The conventional approaches,which are mostly based on the distribution of the pulse energy spectrum,do not well determine the locations and shapes of the pulses. In this paper,we propose a time domain method to reconstruct pulse signals. In the proposed approach,a sparse representation model is established to deal with the issue of the pulse signal recovery under noise conditions. The corresponding problem based on the sparse optimization model is solved by a matching pursuit algorithm. Simulations and experiments validate the effectiveness of the proposed approach on pulse signal recovery.
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机译:Closure to 'Skeletonizing Pipes in Series within Urban Water Distribution Systems Using a Transient-Based Method' by Yuan Huang, Feifei Zheng, Huan-Feng Duan, Tuqiao Zhang, Xinlei Guo, and Qingzhou Zhang
机译:Discussion of 'Skeletonizing Pipes in Series within Urban Water Distribution Systems Using a Transient-Based Method' by Yuan Huang, Feifei Zheng, Huan-Feng Duan, Tuqiao Zhang, Xinlei Guo, and Qingzhou Zhang
机译:metodi microbiologici Tradizionali e metodi moleculeolari per l'analisi degli integratori alimentari a base di o con probiotici per ujso umano(microbiological and molecular methods for analysis of probiotic Based Food supplements for Human Consumption)。