Abstract—The design and optimization of rateless codes for Slepian-Wolf encoding are considered. Rateless codes are pro-posed to address two shortcomings of currently available Slepian-Wolf schemes: their fragility to changing source statistics, and their inability to guarantee successful decoding

Abstract — We provide a novel achievability proof of the Slepian-Wolf theorem for i.i.d. sources over finite alphabets. We demonstrate that random codes that are linear over the real field achieve the classical Slepian-Wolf rate region. For finite alphabets we show that decoding is equivalent

Abstract—We characterize second-order coding rates (or dis-persions) for distributed lossless source coding (the Slepian-Wolf problem). We introduce a fundamental quantity known as the entropy dispersion matrix, which is analogous to scalar dispersion quantities. We show that if this matrix

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We describe a method to encode fingerprint biometrics securely for use, e.g., in encryption or access control. The system is secure because the stored data suffices to validate a probe fingerprint but not to recreate the original fingerprint biometric. Therefore, a breach in database security does not lead to the loss of biometric data. We present a model for a secure biometric system for which we can make strong encryption-like security guarantees. We derive a fundamental trade off between system security and the robustness of authentication. The trade off is quantified for simple statistical models. We outline an implementation and report the effectiveness of our method as tested on a data base consisting of 579 datasets, each containing roughly 15 measurements of a single finger. Workshop on Information Theory and Applications

The key ideas in the theory of broadcast channels are illustrated by discussing some of the progress toward finding the capacity region. The capacity region is still unknown. Index Terms---Binning, broadcast channel, capacity, degraded broadcast channel, feedback capacity, Slepian--Wolf

We present a strategy for Slepian-Wolf coding when the joint distribution of the sources is unknown. The encoders use an incremental transmission policy, and the decoder a universal sequential decision test. We show that the decoder is able to decode shortly after the rates of transmission exceed

to its corresponding sink nodes, and (b) the rate allocation across the source nodes, which is done by Slepian-Wolf coding. We show that the overall minimization can be achieved in two concatenated steps.

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Abstract. Usually, a proof of a theorem contains more knowledge than the mere fact that the theorem is true. For instance, to prove that a graph is Hamiltonian it suffices to exhibit a Hamiltonian tour in it; however, this seems to contain more knowledge than the single bit Hamiltonian