Results 251 to 260 of about 59,031 (278)

On the Free Distance of Convolutional Turbo Codes

2006 IEEE International Symposium on Information Theory, 2006
The free distance of convolutional codes is the most important parameter determining their performance under good channel conditions. In this paper, we investigate the free distance properties of turbo-like codes generated by non-terminated convolutional encoders and convolutional permutors.
Axel Hübner, Kamil Sh. Zigangirov, Daniel J. Costello Jr.   +2 more
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Fractional free convolution powers

Indiana University Mathematics Journal, 2022
Summary: The extension \(k\mapsto\mu^{\boxplus k}\) of the concept of a free convolution power to the case of non-integer \(k\geq1\) was introduced by \textit{H. Bercovici} and \textit{D. Voiculescu} [Probab. Theory Relat. Fields 103, No. 2, 215--222 (1995; Zbl 0831.60036)] and \textit{A. Nica} and \textit{R. Speicher} [Am. J. Math. 118, No.
Shlyakhtenko, Dimitri, Tao, Terence
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DC-free binary convolutional coding

2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060), 2002
Summary: A novel DC-free binary convolutional coding scheme is presented. The proposed scheme achieves the DC-free coding and error-correcting capability simultaneously. The scheme has the simple cascaded structure of the running digital sum (RDS) control encoder and the conventional convolutional encoder.
Tadashi Wadayama, A. J. Han Vinck
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Free distance bounds for convolutional codes

IEEE Transactions on Information Theory, 1974
The best asymptotic bounds presently known on free distance for convolutional codes are presented from a unified point of view. Upper and lower bounds for both time-varying and fixed codes are obtained. A comparison is made between bounds for nonsystematic and systematic codes which shows that more free distance is available with nonsystematic codes ...
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INFINITE DIVISIBILITY FOR THE CONDITIONALLY FREE CONVOLUTION

Infinite Dimensional Analysis, Quantum Probability and Related Topics, 2007
Infinite divisibility for the free additive convolution was studied in Ref. 20. A complete characterization of [Formula: see text]-infinitely divisible distributions was given, and it was explained in Ref. 21 that this characterization is an analogue of the classical Lévy–Khintchine characterization.
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THE NUMBER OF PURE CONVOLUTIONS ARISING FROM CONDITIONALLY FREE CONVOLUTION

Infinite Dimensional Analysis, Quantum Probability and Related Topics, 2005
We show that there are eight special cases of the conditionally free convolution of Bożejko, Leinert and Speicher with the property that in the corresponding moment-cumulant formula no nontrivial weights appear. All the eight convolutions are given. These include the free, the boolean and the Fermi convolutions, another special case of the bold t-free
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A note on the free distance of a convolutional code

1969
A counterexample to a conjecture on the number of constraint lengths required to achieve the free distance of a rate l/n systematic convolutional code is presented.
Miczo, Alexander, Rudolph, Luther D.
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A Class of Dc-Free Subcodes of Convolutional Codes

Proceedings. IEEE International Symposium on Information Theory, 1996
We describe a class of DC-free subcodes of convolutional codes that satisfy certain runlength constraints and that also possess error-correcting capability. The running disparity and the maximum runlength of these codes are bounded by quantities that are independent of the free distance.
Masoumeh Nasiri-Kenari, Craig K. Rushforth   +1 more
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DC-free convolutional codes and DC-free turbo codes

IEEE International Conference on Communications, 2005. ICC 2005. 2005, 2005
In this paper we integrate convolutional/turbo encoding with multimode encoding to generate dc-free convolutional/turbo codes. Based on the generators of error-control codes, we employ flipping or puncturing to ensure that the coded sequences are dc-balanced.
Fengqin Zhai, Yan Xin 0002, Ivan J. Fair
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Regularity Questions for Free Convolution

1998
Free additive convolution is a binary operation on the set M of all probability measures on the real line R. This operation was first defined in [7] for measures with finite moments of all orders (in particular for compactly supported measures). Maassen [5] extended this operation to measures with finite variance, and the extension to arbitrary ...
Hari Bercovici, Dan Voiculescu
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