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References in periodicals archive ?
Different schemes were introduced with DSC such as LDPC [64] code, PRISM [75], Stanford [75], but all these schemes were based on Slepian-Wolf (SW) and Wyner-Ziv (WZ) theorems that increase the range of DSC to many potential applications (sensor network, wireless video) [79].
Sandeep, "Distributed Code Constructions For The Entire Slepian-Wolf Rate Region For Arbitrarily Correlated Sources", Data Compression Conference-DCC, pp.
Zeng, "Power-efficient rate allocation for Slepian-Wolf coding over wireless sensor networks".
Zheng, "A Slepian-Wolf coding based energy-efficient clustering algorithm for data aggregation in wireless sensor networks", ICC, pp.
Jun , "Distributed Data Aggregation Using Clustered Slepian-Wolf Coding, Wireless Sensor Networks", Communications, IEEE International Conference-ICC, pp.
Olmo, "Distributed Arithmetic Coding for the Slepian-Wolf problem", IEEE Transactions on Signal Processing--TSP , vol.
En-Hui-H, "On the linear codebook-level duality between slepian-wolf coding and channel coding.
The complement of Slepian-Wolf coding for lossy compression is the Wyner-Ziv (WZ) coding [3] which deals with lossy source coding of X with side information (SI) Y at the decoder and can reduce complexity of the encoder by shifting ME and MC to the decoder.
Researchers would later use the Slepian-Wolf theorem to develop computer networks.
While conventional video codecs employ motion estimation at the encoder side, the theory developed by Slepian-Wolf [2] leads to a video codec in which temporal prediction is performed at the decoder side.
The Slepian-Wolf coding method is based on Shannon's information theory [2].
Signal X is quantized, and the quantized signal is coded with the Slepian-Wolf encoder.