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Related papers: Reduction of Error-Trellises for Tail-Biting Convo…

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In this paper, we present an error-trellis construction for tailbiting convolutional codes. A tailbiting error-trellis is characterized by the condition that the syndrome former starts and ends in the same state. We clarify the…

Information Theory · Computer Science 2012-01-24 Masato Tajima , Koji Okino

In this paper, we show that the code-trellis and the error-trellis for a convolutional code can be reduced simultaneously, if reduction is possible. Assume that the error-trellis can be reduced using shifted error-subsequences. In this…

Information Theory · Computer Science 2015-05-27 Masato Tajima , Koji Okino , Takashi Miyagoshi

Basic properties of a characteristic matrix for a tail-biting convolutional code are investigated. A tail-biting convolutional code can be regarded as a linear block code. Since the corresponding scalar generator matrix Gt has a kind of…

Information Theory · Computer Science 2017-05-25 Masato Tajima

Let H(D) be the parity-check matrix of an LDPC convolutional code corresponding to the parity-check matrix H of a QC code obtained using the method of Tanner et al. We see that the entries in H(D) are all monomials and several rows…

Information Theory · Computer Science 2009-01-08 M. Tajima , K. Okino , T. Miyagoshi

We consider the decoding of convolutional codes using an error trellis constructed based on a submatrix of a given check matrix. In the proposed method, the syndrome-subsequence computed using the remaining submatrix is utilized as…

Information Theory · Computer Science 2010-01-09 Masato Tajima , Koji Okino , Takashi Miyagoshi

Tail-biting convolutional codes extend the classical zero-termination convolutional codes: Both encoding schemes force the equality of start and end states, but under the tail-biting each state is a valid termination. This paper proposes a…

Information Theory · Computer Science 2021-02-03 Tomer Raviv , Asaf Schwartz , Yair Be'ery

This paper investigates tail-biting trellis realizations for linear block codes. Intrinsic trellis properties are used to characterize irreducibility on given intervals of the time axis. It proves beneficial to always consider the trellis…

Information Theory · Computer Science 2012-12-18 Heide Gluesing-Luerssen , G. David Forney

In this paper, embedding construction of tail-biting trellises for linear block codes is presented. With the new approach of constructing tail-biting trellises, most of the study of tail-biting trellises can be converted into the study of…

Information Theory · Computer Science 2011-09-07 Jianqin Zhou

A linear time approximate maximum likelihood decoding algorithm on tail-biting trellises is prsented, that requires exactly two rounds on the trellis. This is an adaptation of an algorithm proposed earlier with the advantage that it reduces…

Information Theory · Computer Science 2008-02-07 K. Murali Krishnan , Priti Shankar

Simple rate-1/3 single-error-correcting unrestricted and CSS-type quantum convolutional codes are constructed from classical self-orthogonal $\F_4$-linear and $\F_2$-linear convolutional codes, respectively. These quantum convolutional…

Quantum Physics · Physics 2016-11-17 G. David Forney, , Saikat Guha

The multidimensional convolutional codes are an extension of the notion of convolutional codes (CCs) to several dimensions of time. This paper explores the class of two-dimensional convolutional codes (2D CCs) and 2D tail-biting…

Information Theory · Computer Science 2011-09-20 Liam Alfandary , Dan Raphaeli

Cyclic redundancy check (CRC) codes combined with convolutional codes yield a powerful concatenated code that can be efficiently decoded using list decoding. To help design such systems, this paper presents an efficient algorithm for…

Information Theory · Computer Science 2020-05-19 Hengjie Yang , Linfang Wang , Vincent Lau , Richard D. Wesel

We propose two approximate algorithms for MAP decoding on tail-biting trellises. The algorithms work on a subset of nodes of the tail-biting trellis, judiciously selected. We report the results of simulations on an AWGN channel using the…

Information Theory · Computer Science 2007-07-13 A. S. Madhu , Priti Shankar

An algorithm for exact maximum likelihood(ML) decoding on tail-biting trellises is presented, which exhibits very good average case behavior. An approximate variant is proposed, whose simulated performance is observed to be virtually…

Information Theory · Computer Science 2007-07-13 Priti Shankar , P. N. A. Kumar , K. Sasidharan , B. S. Rajan , A. S. Madhu

Trellises provide a graphical representation for the row space of a matrix. The product construction of Kschischang and Sorokine builds minimal conventional trellises from matrices in minimal span form. Koetter and Vardy showed that minimal…

Information Theory · Computer Science 2015-09-29 Iwan M. Duursma

Rate-(n-2)/n unrestricted and CSS-type quantum convolutional codes with up to 4096 states and minimum distances up to 10 are constructed as stabilizer codes from classical self-orthogonal rate-1/n F_4-linear and binary linear convolutional…

Quantum Physics · Physics 2012-08-27 G. David Forney, , Markus Grassl , Saikat Guha

The A* algorithm is a graph search algorithm which has shown good results in terms of computational complexity for Maximum Likelihood (ML) decoding of tailbiting convolutional codes. The decoding of tailbiting codes with this algorithm is…

Information Theory · Computer Science 2025-01-28 Jorge Ortin , Paloma Garcia , Fernando Gutierrez , Antonio Valdovinos

Trellises are crucial graphical representations of codes. While conventional trellises are well understood, the general theory of (tail-biting) trellises is still under development. Iterative decoding concretely motivates such theory. In…

Information Theory · Computer Science 2014-02-27 David Conti , Nigel Boston

Recently, rate-1/n zero-terminated (ZT) and tail-biting (TB) convolutional codes (CCs) with cyclic redundancy check (CRC)-aided list decoding have been shown to closely approach the random-coding union (RCU) bound for short blocklengths.…

Information Theory · Computer Science 2023-10-11 Wenhui Sui , Brendan Towell , Ava Asmani , Hengjie Yang , Holden Grissett , Richard D. Wesel

We study the finite-time behaviour of the popular temporal difference (TD) learning algorithm when combined with tail-averaging. We derive finite time bounds on the parameter error of the tail-averaged TD iterate under a step-size choice…

Machine Learning · Computer Science 2024-09-20 Gandharv Patil , Prashanth L. A. , Dheeraj Nagaraj , Doina Precup
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