Information Theory: Coding Theorems for Discrete Memoryless Systems

By Imre Csiszár, J. Körner. 2011

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Citations in the corpus

Information-Theoretic Lower Bounds on Bayes Risk in Decentralized Estimation (2016, positive): “In particular [30, Problem 10.36], From the lower bound in (104) and the upper bound in (107), we know that the Bayes risk in this case decays polynomially in n and exponentially in T .”
Information Spectrum Approach to Second-Order Coding Rate in Channel Coding (2008, background): “The maximum coding rate with the above condition is called the capacity with the cost constraint, and is given by [10]”
Secure Multiterminal Source Coding With Side Information at the Eavesdropper (2011, unknown): “Delta-Convention [63]:For any setsX , Y , there exists a sequence {δn}n∈N∗ such that lemmas below hold.”
Improved Natural Language Generation via Loss Truncation (2020, background): “For log loss, Pinsker’s inequality (Csiszar and Körner, 2011) relates the KL divergence and distinguishability as”
Energy Harvesting Wireless Communications: A Review of Recent Advances (2015, background): “The information-energy transfer formulation is also mathematically similar 3.15 3.16 3.17 to the classical problem of cost-constrained capacity in [92, Thm. 6.11] and [93, Thm. 3.7.2].”
Universal Estimation of Information Measures for Analog Sources (2009, methodology): “The f -divergence is a family of distance measures introduced by Csiszár [59, 62, 63] and independently by Ali and Silvey [10].”
Advances in quantum cryptography (2019, unknown): “[50] I.”
A Survey on Quantum Channel Capacities (2018, background): “A very important result regarding the compression of classical information was published by Csiszár and Körner in 1978 [117], and later the authors published a great book about coding theorems for discrete memoryless systems [118].”
Differentiable Compositional Kernel Learning for Gaussian Processes (2018, background): “…positive function g ( x ) and (cid:15) > 0 , the Gaussian mixture approximation theorem ensures existing According to Pinsker’s Inequality (Csiszar & K¨orner, 2011), for two probability distributions P, Q , For small enough d v and d µ , we have Thus, the L 1 norm between two gaussians…”