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The Research of Compressed Sensing Algorithm in Things of Mine

Author: DuJuan
Tutor: QiuXiaoZuo
School: Nanjing University of Posts and Telecommunications
Course: Signal and Information Processing
Keywords: Mine of Things Compressed sensing Bayesian estimation Logical space
CLC: TN929.5
Type: Master's thesis
Year: 2011
Downloads: 324
Quote: 0
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Abstract


The coal mines of Things as an emerging hot research field , integrated sensor technology , micro- electromechanical systems technology , wireless communication technology and distributed information processing technology . It will of Things technology applications in the coal mine environment , underground work to improve the visibility and security , mine has changed the traditional practices . Compressed sensing theory for signal acquisition technology brings a revolutionary breakthrough , far below the Nyquist frequency of the signal is sampled by numerical optimization methods to accurately reconstruct the original signal . Despite the compressed sensing theory is not perfect , but its presence has set off a wave of research boom in signal processing and other fields , provide new ideas and new ways for the many unsolved problem . Compressed sensing theory has a strong vitality , will create a more broad application prospects . From compressed sensing algorithm , this paper introduces the theory of compressed sensing technology in the coal mines of Things advantage relative to other data fusion , and analysis of the problems existing in the compressed sensing theory . For coal Internet of Things application environment , improved method , which is based on the theory of wavelet transform LSC-CS , the algorithm through a matrix of logically related data were wavelet row transform and wavelet column transform to remove data correlation and spatial correlation, and to reduce the data in the transmission, storage , and other aspects of energy consumption has important significance . Finally , Matlab simulation platform based simulated mine environment , with LSC-CS algorithm based on wavelet transform data such as temperature , humidity simulation, test algorithm improved performance in energy consumption , reliability and validity , and a comparative analysis with traditional algorithms , and prove that the improved algorithm for signal reconstruction accuracy also significantly improved in terms of energy consumption .

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