Data processing lower bounds for scalar lossy source codes with side information at the decoder
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[1] A. Rényi. On Measures of Entropy and Information , 1961 .
[2] Ram Zamir,et al. A Ziv-Zakai-Rényi lower bound on distortion at high resolution , 2008, 2008 IEEE Information Theory Workshop.
[3] Wei Yu,et al. Blahut-Arimoto algorithms for computing channel capacity and rate-distortion with side information , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..
[4] Neri Merhav,et al. Data-Processing Bounds for Scalar Lossy Source Codes With Side Information at the Decoder , 2013, IEEE Transactions on Information Theory.
[5] Neri Merhav,et al. Data Processing Theorems and the Second Law of Thermodynamics , 2010, IEEE Transactions on Information Theory.
[6] Neri Merhav,et al. Efficient On-Line Schemes for Encoding Individual Sequences With Side Information at the Decoder , 2009, IEEE Transactions on Information Theory.
[7] Meir Feder,et al. Distortion lower bounds for finite dimensional joint source-channel coding , 2008, 2008 IEEE International Symposium on Information Theory.
[8] Neri Merhav,et al. On successive refinement for the Wyner-Ziv problem , 2004, ISIT.
[9] Sergio D. Servetto,et al. Lattice quantization with side information , 2000, Proceedings DCC 2000. Data Compression Conference.
[10] Ertem Tuncel,et al. Low-Delay Prediction- and Transform-Based Wyner–Ziv Coding , 2011, IEEE Transactions on Signal Processing.
[11] J. Ziv,et al. A Generalization of the Rate-Distortion Theory and Applications , 1975 .
[12] Jacob Ziv,et al. On functionals satisfying a data-processing theorem , 1973, IEEE Trans. Inf. Theory.
[13] Michelle Effros,et al. Quantization as Histogram Segmentation: Optimal Scalar Quantizer Design in Network Systems , 2008, IEEE Transactions on Information Theory.
[14] Ertem Tuncel,et al. High-resolution predictive Wyner-Ziv coding of Gaussian sources , 2009, 2009 IEEE International Symposium on Information Theory.
[15] Demosthenis Teneketzis,et al. On the Structure of Optimal Real-Time Encoders and Decoders in Noisy Communication , 2006, IEEE Transactions on Information Theory.
[16] J. Kusuma. Slepian-Wolf Coding and Related Problems , 2022 .
[17] Zixiang Xiong,et al. Successive refinement for the Wyner-Ziv problem and layered code design , 2005, IEEE Trans. Signal Process..
[18] Zixiang Xiong,et al. Distributed source coding for sensor networks , 2004, IEEE Signal Processing Magazine.
[19] R. Gallager. Information Theory and Reliable Communication , 1968 .
[20] Sergio D. Servetto,et al. Lattice Quantization With Side Information: Codes, Asymptotics, and Applications in Sensor Networks , 2006, IEEE Transactions on Information Theory.
[21] Kannan Ramchandran,et al. Distributed compression for sensor networks , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).
[22] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[23] Ram Zamir,et al. Bounds for joint source-channel coding at high SNR , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.
[24] Ertem Tuncel,et al. Low-delay quantization for source coding with side information , 2008, 2008 IEEE International Symposium on Information Theory.
[25] Neri Merhav,et al. Structure Theorems for Real-Time Variable Rate Coding With and Without Side Information , 2011, IEEE Transactions on Information Theory.
[26] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .