The redundancy of source coding with a fidelity criterion: 1. Known statistics
暂无分享,去创建一个
Zhen Zhang | En-Hui Yang | Victor K.-W. Wei | Zhen Zhang | V. Wei | E. Yang
[1] Robert B. Ash,et al. Information Theory , 2020, The SAGE International Encyclopedia of Mass Media and Society.
[2] J. Rissanen. Stochastic Complexity and Modeling , 1986 .
[3] Jorma Rissanen,et al. Density estimation by stochastic complexity , 1992, IEEE Trans. Inf. Theory.
[4] Katalin Marton,et al. A simple proof of the blowing-up lemma , 1986, IEEE Trans. Inf. Theory.
[5] Marcelo J. Weinberger,et al. Upper bounds on the probability of sequences emitted by finite-state sources and on the redundancy of the Lempel-Ziv algorithm , 1992, IEEE Trans. Inf. Theory.
[6] Peter Elias,et al. Universal codeword sets and representations of the integers , 1975, IEEE Trans. Inf. Theory.
[7] Zhen Zhang,et al. An on-line universal lossy data compression algorithm via continuous codebook refinement - Part I: Basic results , 1996, IEEE Trans. Inf. Theory.
[8] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[9] Andrew R. Barron,et al. Information-theoretic asymptotics of Bayes methods , 1990, IEEE Trans. Inf. Theory.
[10] Frederick Jelinek,et al. On variable-length-to-block coding , 1972, IEEE Trans. Inf. Theory.
[11] Jorma Rissanen,et al. Complexity of strings in the class of Markov sources , 1986, IEEE Trans. Inf. Theory.
[12] R. Gray,et al. A Generalization of Ornstein's $\bar d$ Distance with Applications to Information Theory , 1975 .
[13] D. Ornstein,et al. Universal Almost Sure Data Compression , 1990 .
[14] Mark H. A. Davis,et al. Strong Consistency of the PLS Criterion for Order Determination of Autoregressive Processes , 1989 .
[15] Lee D. Davisson,et al. Minimax noiseless universal coding for Markov sources , 1983, IEEE Trans. Inf. Theory.
[16] Neri Merhav. A comment on 'A rate of convergence result for a universal D-semifaithful code' , 1995, IEEE Trans. Inf. Theory.
[17] R. Gray. Entropy and Information Theory , 1990, Springer New York.
[18] Jorma Rissanen,et al. Universal coding, information, prediction, and estimation , 1984, IEEE Trans. Inf. Theory.
[19] John C. Kieffer,et al. A unified approach to weak universal source coding , 1978, IEEE Trans. Inf. Theory.
[20] Robert M. Gray,et al. Source coding theorems without the ergodic assumption , 1974, IEEE Trans. Inf. Theory.
[21] Zhen Zhang,et al. An on-line universal lossy data compression algorithm via continuous codebook refinement - Part II. Optimality for phi-mixing source models , 1996, IEEE Trans. Inf. Theory.
[22] Tamás Linder,et al. Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding , 1994, IEEE Trans. Inf. Theory.
[23] P. Gács,et al. Bounds on conditional probabilities with applications in multi-user communication , 1976 .
[24] Andrew R. Barron,et al. Minimum complexity density estimation , 1991, IEEE Trans. Inf. Theory.
[25] Raphail E. Krichevsky,et al. The performance of universal encoding , 1981, IEEE Trans. Inf. Theory.
[26] Lee D. Davisson,et al. Universal noiseless coding , 1973, IEEE Trans. Inf. Theory.
[27] David L. Neuhoff,et al. Fixed rate universal block source coding with a fidelity criterion , 1975, IEEE Trans. Inf. Theory.
[28] En-Hui Yang,et al. Simple universal lossy data compression schemes derived from the Lempel-Ziv algorithm , 1996, IEEE Trans. Inf. Theory.
[29] E. J. Hannan,et al. REGRESSION, AUTOREGRESSION MODELS , 1986 .
[30] Michael B. Pursley,et al. Variable-rate universal block source coding subject to a fidelity constraint , 1978, IEEE Trans. Inf. Theory.
[31] R. J. Pilc. The transmission distortion of a source as a function of the encoding block length , 1968 .
[32] Bin Yu,et al. A rate of convergence result for a universal D-semifaithful code , 1993, IEEE Trans. Inf. Theory.