J. Wolf

Publications
Influence

Noiseless coding of correlated information sources

D. Slepian, J. Wolf
Mathematics, Computer Science
IEEE Trans. Inf. Theory
1 September 1973

We determine the minimum number of bits per character R_X and R_Y needed to encode these sequences so that they can be faithfully reproduced under a variety of assumptions regarding the encoders and decoders. Expand

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Characterizing flash memory: Anomalies, observations, and applications

Laura M. Grupp, A. Caulfield, +4 authors J. Wolf
Computer Science
42nd Annual IEEE/ACM International Symposium on…
12 December 2009

This paper empirically characterizes flash memory technology by measuring the performance, power, and reliability of flash devices from five manufacturers. Expand

Efficient maximum likelihood decoding of linear block codes using a trellis

J. Wolf
Computer Science
IEEE Trans. Inf. Theory
1978

It is shown that soft decision maximum likelihood decoding of any (n,k) linear block code over GF(q) can be accomplished using the Viterbi algorithm applied to a trellis with no more than q^{(n-k)} states. Expand

Windowed Decoding of Protograph-Based LDPC Convolutional Codes Over Erasure Channels

A. Iyengar, M. Papaleo, P. Siegel, J. Wolf, A. Vanelli-Coralli, G. Corazza
Computer Science, Mathematics
IEEE Transactions on Information Theory
21 October 2010

We show that the structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding. Expand

Transmission of noisy information to a noisy receiver with minimum distortion

J. Wolf, J. Ziv
Computer Science
IEEE Trans. Inf. Theory
1 July 1970

This paper is concerned with the transmission of information with a fidelity criterion where the source output may be distorted prior to encoding and, furthermore, where the output of the decoder may be distortion prior to delivery to the final destination. Expand

The capacity region of a multiple-access discrete memoryless channel can increase with feedback (Corresp.)

N. Gaarder, J. Wolf
Computer Science
IEEE Trans. Inf. Theory
1975

The capacity of a single-input single-output discrete memoryless channel is not increased by the use of a noiseless feedback link. Expand

Finite-State Modulation Codes for Data Storage

B. Marcus, P. Siegel, J. Wolf
Computer Science
IEEE J. Sel. Areas Commun.
1992

The authors provide a self-contained exposition of modulation code design methods based upon the state splitting algorithm for constructing finite state encoders. Expand

Codes for Digital Recorders

Kees A. Schouhamer Immink, P. Siegel, J. Wolf
Computer Science
IEEE Trans. Inf. Theory
1 October 1998

This paper surveys the theory and practice of constrained coding, tracing the evolution of the subject from its origins in Shannon's classic 1948 paper to present-day applications in high-density digital recorders. Expand

Permutation codes for sources

T. Berger, F. Jelinek, J. Wolf
Mathematics, Computer Science
IEEE Trans. Inf. Theory
1972

Source encoding techniques based on permutation codes are investigated. For a broad class of distortion measures it is shown that optimum encoding of a source permutation code is easy to instrument… Expand

Turbo decoding for PR4: parallel versus serial concatenation

T. Souvignier, A. Friedmann, Mats Öberg, P. Siegel, R. Swanson, J. Wolf
Computer Science
IEEE International Conference on Communications…
6 June 1999

A simplified serial concatenation system is presented that uses as its outer code a single convolutional code and as its inner code the partial response channel. Expand

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