Distributed video coding is an emerging area of research for digital video driven partly by the widespread use of video acquisition devices by the consumers. In this paper, we present a distributed video coding scheme based on zero motion identification at the decoder and constrained rate adaptive low density parity check (LDPC) codes. Zero-motion-block identification mechanism is introduced at the decoder, which takes the characters of video sequence into account. The constrained error control decoder can use the bits in the zero motion blocks as a constraint to achieve a better decoding performance and further improve the overall video compression efficiency. It is only at the decoder side that the proposed scheme exploits temporal and spatial redundancy without introducing any additional processing at the encoder side, which keeps the complexity of the encoding as low as possible with certain compression efficiency. As a powerful alternative to Turbo codes, LDPC codes have been applied to our scheme. Since video data are highly non-ergodic, we use rate-adaptive LDPC codes to fit this variation of the achievable compression rate in our scheme. But one most basic difference between LDPC codes in our scheme and conventional channel coding is that in our scheme, we can make sure some bits are known. Those bits can work as constraints to the decoder and improve the decoding performance. We propose a constrained LDPC decoder not only to improve the decoder efficiency but also to speed the convergence of the iterative decoding. Simulation demonstrates that the scheme has significant improvement in the performances. In addition, the proposed constrained LDPC decoder may benefit other application.
In recent years, with the continued growth of energy demand, intelligent grid has become the common choice for the global power industry to meet the challenges of the future. In order to achieve a high degree of integration of the intelligent grid and the Internet of things, based on a brief introduction of related theories and techniques, through the research on the functional characteristics of the Internet of things and its application status in power grid, the framework of the whole life cycle management of power equipment based on Internet of things was constructed, and its management advantages were analyzed in detail. Experimental results show that this system can provide a high degree of integration of intelligent grid and Internet of things.
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