Weaknesses of Margulis and Ramanujan-Margulis low-density parity-check codes

We report weaknesses in two algebraic constructions of low-density parity-check codes based on expander graphs. The Margulis construction gives a code with near-codewords, which cause problems for the sum-product decoder; The Ramanujan-Margulis construction gives a code with low-weight codewords, which produce an error-floor. © 2004 Elsevier B.V.

Performance of low density parity check codes as a function of actual and assumed noise levels

We investigate how sensitive Gallager's codes are, when decoded by the sum-product algorithm, to the assumed noise level. We have found a remarkably simple function that fits the empirical results as a function of the actual noise level at both high and low noise levels. © 2004 Elsevier B.V.

Performance of low density parity check codes as a function of actual and assumed noise levels

We investigate how sensitive Gallager's codes are, when decoded by the sum-product algorithm, to the assumed noise level. We have found a remarkably simple function that fits the empirical results as a function of the actual noise level at both high and low noise levels. ©2003 Published by Elsevier Science B. V.

Weaknesses of margulis and ramanujan-margulis low-density parity-check codes

We report weaknesses in two algebraic constructions of low-density parity-check codes based on expander graphs. The Margulis construction gives a code with near-codewords, which cause problems for the sum-product decoder; The Ramanujan-Margulis construction gives a code with low-weight codewords, which produce an error-floor. ©2003 Published by Elsevier Science B. V.

Comparison of constructions of irregular Gallager codes

The low-density parity check codes whose performance is closest to the Shannon limit are `Gallager codes' based on irregular graphs. We compare alternative methods for constructing these graphs and present two results. First, we find a `super-Poisson' construction which gives a small improvement in empirical performance over a random construction. Second, whereas Gallager codes normally take N2 time to encode, we investigate constructions of regular and irregular Gallager codes that allow more rapid encoding and have smaller memory requirements in the encoder. We find that these `fast encoding' Gallager codes have equally good performance.

Engineering development of the Lancaster flexible bag.

Describes progress in the last 12 months which has established bag designs and fabrication techniques, giving greater confidence in the life and cost of these components. A quarter scale bag is under construction. Extensive tank testing has also established life time bending moment and mooring load envelopes, enabling hull and mooring design to proceed. A computer simulation programme has been used to check tank model results and to establish turbine and generator operating conditions. This has allowed generation and transmission component design to proceed, and suggests a high operating efficiency can be maintained with a simple control regime. Simple solutions in minor areas such as valve design and damage stability control add to the picture of steady progress in establishing the Lancaster Flexible Bag 's feasibility.

Structured discriminative models for noise robust continuous speech recognition

Recently there has been interest in structured discriminative models for speech recognition. In these models sentence posteriors are directly modelled, given a set of features extracted from the observation sequence, and hypothesised word sequence. In previous work these discriminative models have been combined with features derived from generative models for noise-robust speech recognition for continuous digits. This paper extends this work to medium to large vocabulary tasks. The form of the score-space extracted using the generative models, and parameter tying of the discriminative model, are both discussed. Update formulae for both conditional maximum likelihood and minimum Bayes' risk training are described. Experimental results are presented on small and medium to large vocabulary noise-corrupted speech recognition tasks: AURORA 2 and 4. © 2011 IEEE.