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Improved distributed compressed sensing for smooth signals in wireless sensor networks

机译:改进的分布式压缩感测,可实现无线传感器网络中的平滑信号

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The technology of the distributed compressed sensing is thought as an extension of compressed sensing and it makes applying multiple signals into compressed sensing possible. A vital issue in distributed compressed sensing is to minimize the difference between the original signal and the recovery signal. In this paper, we improve the distributed compressed sensing for smooth signals in wireless sensor networks. Firstly, we put forward a new weighted method to obtain the common component of all signals, and then one method of lossy coding for shortening the length of common component is proposed. Most importantly, we improve the calculation formula of the distributed compressed sensing to ensure that the common component can be received losslessly. The numerical results show that, comparing with the distributed compressed sensing, the improved distributed compressed sensing not only can use much fewer measurements to recover the original signal, but also enable the effect of signal recovery to be better than that of traditional distributed compressed sensing.
机译:分布式压缩感测技术被认为是压缩感测的扩展,它使将多个信号应用于压缩感测成为可能。分布式压缩感测中的关键问题是最小化原始信号和恢复信号之间的差异。在本文中,我们针对无线传感器网络中的平滑信号改进了分布式压缩感知。首先,提出了一种新的加权方法来获取所有信号的公共分量,然后提出了一种缩短公共分量长度的有损编码方法。最重要的是,我们改进了分布式压缩感知的计算公式,以确保可以无损地接收公共分量。数值结果表明,与分布式压缩感知相比,改进的分布式压缩感知不仅可以使用更少的测量量来恢复原始信号,而且使信号恢复的效果要好于传统的分布式压缩感知。

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