A method that effectively reduces the weight of parity checks used in iterative probabilistic decoding algorithms is proposed. The method is especially applicable to so-called parity checks with memory and may lead to...
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A method that effectively reduces the weight of parity checks used in iterative probabilistic decoding algorithms is proposed. The method is especially applicable to so-called parity checks with memory and may lead to a significant improvement in fast correlation attacks on stream ciphers based on linear feedback shift registers. A technique for generating low-weight parity checks with memory is also proposed.
We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay-Neal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but a...
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We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay-Neal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties. The decoding of both codes can be tackled with a practical sum-product algorithm. We prove that these codes are "very good," in that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit. This result holds not only for the binary-symmetric channel but also for any channel with symmetric stationary ergodic noise. We give experimental results for binary-symmetric channels and Gaussian channels demonstrating that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved;indeed, the performance of Gallager codes is almost as close to the Shannon limit as that of turbo codes.
A new, vectorial approach to fast correlation attacks on binary memoryless combiners is proposed. Instead of individual input sequences or their linear combinations, the new attack is targeting subsets of input sequen...
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A new, vectorial approach to fast correlation attacks on binary memoryless combiners is proposed. Instead of individual input sequences or their linear combinations, the new attack is targeting subsets of input sequences as a whole thus exploiting the full correlation between the chosen subset and the output sequence. In particular, the set of all the input sequences can be chosen as the target. The attack is based on a novel iterativeprobabilistic algorithm which is also applicable to general memoryless combiners over finite fields or finite rings. To illustrate the effectiveness of the introduced approach, experimental results obtained for random balanced combining functions are presented
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 t...
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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 N-2 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.
Gallager's low-density binary parity check codes have been shown to have near-Shannon limit performance when decoded using a probabilisticdecoding algorithm. We report the empirical results of error-correction us...
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Gallager's low-density binary parity check codes have been shown to have near-Shannon limit performance when decoded using a probabilisticdecoding algorithm. We report the empirical results of error-correction using the analogous codes over GF (q) for q > 2;with binary symmetric channels and binary Gaussian channels. We find a significant improvement over the performance of the binary codes, including a rate 1/4 code with bit error probability < 10(-5) at E(b)/N(0) = 0.2 dB.
We propose an iterativeprobabilistic algorithm for estimation of RNA secondary structure using sequence data from two homologous sequences. The method is intended to exploit inter-sequence correlations "encoded&...
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ISBN:
(纸本)9781424407286
We propose an iterativeprobabilistic algorithm for estimation of RNA secondary structure using sequence data from two homologous sequences. The method is intended to exploit inter-sequence correlations "encoded" in the form of probabilistic models for alignment and for common secondary structure. In analogy with turbo-decoding in digital communications, we formulate a maximum a posteriori probability objective function for joint structural prediction and sequence alignment using iterations over individual structural and sequential alignment models with soft-input soft-output estimators. As a preliminary step toward realizing this methodology, we present results obtained from incorporating (hard) constraints based on posterior sequence alignment probabilities in joint secondary structure prediction. Through experimental evaluations over available databases of known secondary structure, we demonstrate that this results in a significant decrease in computation time while simultaneously providing a marginal increase in structural prediction accuracy.
We study linear unitary precoding for multiple antenna transmissions. Our aim is to find a new precoder satisfying both the genie conditions and the non-vanishing determinant criterion. Such a precoder will be optimiz...
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