1. |
- Afanassiev, Valentin, et al.
(författare)
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Fast authentication codes based on random polynomial residue classes
- 1997
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Ingår i: Proceedings 1997 IEEE International Symposium on Information Theory. - 2157-8095. - 0780339568 - 9780780339569 ; , s. 175-175
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Konferensbidrag (refereegranskat)abstract
- The verification of the authenticity of a text document or a datafile is one of the main applications of cryptographic techniques. A common used technique for this purpose is the application of a message authentication code (MAC). Usually the MAC computation has to be done in software. Based on the relationship between error-correcting codes and so-called families of almost universal hash functions, and the error-correcting codes using polynomial residue classes we describe an efficient procedure for a MAC computation which is much faster than the standard MAC constructions using MD5 or SHA and uses much less key bits than the fast MACs based on bucket hashing.
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2. |
- Höst, Stefan, et al.
(författare)
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Active distances and cascaded convolutional codes
- 1997
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Ingår i: [Host publication title missing]. - 0780339568 ; , s. 107-107
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Konferensbidrag (refereegranskat)abstract
- A family of active distances for convolutional codes is introduced. Lower bounds are derived for the ensemble of periodically time-varying convolutional codes.
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3. |
- Höst, Stefan, et al.
(författare)
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On the distribution of the output error burst lengths for Viterbi decoding of convolutional codes
- 1997
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Ingår i: [Host publication title missing]. - 0780339568 ; , s. 108-108
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Konferensbidrag (refereegranskat)abstract
- The distribution of the output error burst lengths from a Viterbi decoder is of particular interest in connection with concatenated coding systems, where the inner code is convolutional. From the expurgated, random, and sphere-packing exponents for block codes an upper bound on this distribution for the ensemble of periodically time-varying convolutional codes is obtained. Finally, the distribution obtained from simulating time-invariant convolutional codes is presented
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4. |
- Johannesson, Rolf, et al.
(författare)
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Some results on convolutional codes over rings
- 1997
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Ingår i: [Host publication title missing]. - 0780339568 ; , s. 284-284
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Konferensbidrag (refereegranskat)abstract
- Convolutional codes over rings were motivated from phase-modulated signals. Some structural properties of generator matrices of convolutional codes over rings have been studied. A condition for a convolutional code over a ring to be systematic is given and shown to be equivalent to the condition given by Massey and Mittelholzer (1989). Furthermore, the conditions of generator matrices over Z(pe) being catastrophic, basic, and minimal are considered, and the predictable degree property of polynomial generator matrices is considered.
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5. |
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6. |
- Åberg, Jan, et al.
(författare)
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Estimation of escape probabilities for PPM based on universal source coding theory
- 1997
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Ingår i: Proceedings 1997 IEEE International Symposium on Information Theory. - 2157-8095. - 0780339568 - 9780780339569 ; , s. 65-65
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Konferensbidrag (refereegranskat)abstract
- Some of the best compression ratios for text compression are provided by the PPM (prediction by partial matching) class of algorithms. These algorithms are based on arithmetic coding using a fixed-depth Markov chain model of the source, i.e., the subsequence of symbols generated in any state s of the source is assumed to be the output of a memoryless subsource w=w(s). One of the most crucial steps in any PPM algorithm is the choice of the escape probability, i.e., the probability of a previously unseen symbol appearing in a given state. Let A={1,...,M} be the source alphabet, x/sup k/=x/ix/ i...x/sub k//spl isin/A/sup k/ be a sequence of symbols generated by a subsource w with unknown parameters, and m=m(x/sup k/) be the number of different symbols in x/sup k/. In most incarnations of PPM, the expression for the escape probability used for coding is of the form /spl thetav/(E|x/sup k/)=k(k,m)/k+m/spl alpha/+k(k,m), where /spl alpha/ is a parameter. The encoding of the "escape symbol" E is followed by a description of the new symbol, which is independent of the choice of escape probability and is not discussed. In almost all PPM schemes, the expression for the escape probability has been chosen heuristically. Following the method of Shtarkov et al. (see Probl. of Information Transmission, vol.31, no.2, p.20-35, 1995) we use a universal coding approach.
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7. |
- Ödling, Per, et al.
(författare)
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Making MLSD-decisions on some individual symbols in a sequence by thresholding the matched filter output
- 1997
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Ingår i: [Host publication title missing]. - : Institute of Electrical and Electronics Engineers (IEEE). - 0780339568 ; , s. 75-75
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Konferensbidrag (refereegranskat)abstract
- We present a detector that, by thresholding the output of the matched filter, gives MLSD-decisions on binary, antipodally modulated symbols that have been corrupted by intersymbol interference and additive Gaussian noise. The detector is simple in structure, consisting of a whitened matched filter and two variable thresholds for each symbol to be detected. The detector will make decisions on some, but most often not all, of the symbols in a transmitted sequence, and those decisions will be the same decisions as the maximum likelihood sequence detector (MLSD) would have made. The number of symbols that are detected is stochastic, varying from sequence to sequence. The basis of the detector is a bound on a cross-product of the quadratic form in the log-likelihood function for the transmitted sequence
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8. |
- Ödling, Per, et al.
(författare)
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Making MLSD-decisions on some individual symbols thresholding the matched filter output
- 1997
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Ingår i: Proceedings. - Piscataway, NJ : IEEE Communications Society. - 0780339568 ; , s. 75-
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Konferensbidrag (refereegranskat)abstract
- We present a detector that, by thresholding the output of the matched filter, gives MLSD-decisions on binary, antipodally modulated symbols that have been corrupted by intersymbol interference and additive Gaussian noise. The detector is simple in structure, consisting of a whitened matched filter and two variable thresholds for each symbol to be detected. The detector will make decisions on some, but most often not all, of the symbols in a transmitted sequence, and those decisions will be the same decisions as the maximum likelihood sequence detector (MLSD) would have made. The number of symbols that are detected is stochastic, varying from sequence to sequence. The basis of the detector is a bound on a cross-product of the quadratic form in the log-likelihood function for the transmitted sequence
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