Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coin...
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Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coincides with the conditional rate-distortion function. In this paper, we extend the problem to the coding of multivariate Gaussian source with multiple Gaussian side information at the decoder. The achievable region is obtained, and it is easily extended to the case that the difference between the source and the side information is multivariate Gaussian, no matter what distributions the source and the side information are. We apply this theoretical model to distributed Video Coding (DVC) by considering the difference of the distributed frame (D frame) and the Side-information frame (S frame) to be multivariate Gaussian distributed. This introduces rate allocation problem into DVC, which can be solved by a reverse water-filling method. Simulation results show that around 1.5-2 dB coding gain benefits from the multivariate Gaussian Wyner-Ziv coding model.
The avionics system is an important part of modern fighters, and the analysis and processing of large data generated by the avionics system can provide some guidance for the pilot's decision-making. After analyzin...
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ISBN:
(纸本)9781509055074
The avionics system is an important part of modern fighters, and the analysis and processing of large data generated by the avionics system can provide some guidance for the pilot's decision-making. After analyzing the existing distributed framework, a multi-platform avionics data system is designed and implemented to solve the problem that heterogeneous real-time data generated by a large number of sensors is difficult to be managed efficiently. With the help of the cloud platform, the system supports functions of data collection, data classification management, data storage and data analysis. It can establish the related model based on the historical data and it can make real-time prediction with real-time data and correlation model. The test results show that the system functional testing requirements coverage rate is 100%, and performance and stability are both in line with the requirements.
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