Article
On Estimation of the Error Exponent for Finite Length Regular Graph-Based LDPC Codes
The error exponent of the regular graph-based binary low-density parity-check (LDPC) codes under the maximum likelihood (ML) decoding algorithm in the binary symmetric channel (BSC) is analyzed. Unlike most other papers where error exponents are considered for the case when the length of LDPC codes tends to infinity (asymptotic analysis), the finite length case (finite length analysis) is considered. In this paper, a method of deriving the lower bound on the error exponent for a regular graph-based LDPC code with finite length under ML decoding is described. Also we analyze Dependences of the error exponent on various LDPC code parameters are also analyzed. The numerical results obtained for the considered lower bound are represented and analyzed at the end of the paper.
This paper deals with the error exponent of the regular graph-based binary low-density parity-check (LDPC) codes under the maximum likelihood (ML) decoding algorithm in the binary symmetric channel (BSC). Unlike other papers where error exponents are considered for the case when the length of LDPC codes tends to infinity (asymptotic analysis) we considered the finite length case (finite length analysis). In this paper we describe the method of deriving the lower bound on the error exponent for regular graph- based LDPC code with finite length under ML decoding and analyze the dependency of the error exponent on various LDPC code parameters. The numerical results, obtained for the considered lower bound, are represented and analyzed at the end of the paper.
Two ensembles of low-density parity-check (LDPC) codes with low-complexity decoding algorithms are considered. The first ensemble consists of generalized LDPC codes, and the second consists of concatenated codes with an outer LDPC code. Error exponent lower bounds for these ensembles under the corresponding low-complexity decoding algorithms are compared. A modification of the decoding algorithm of a generalized LDPC code with a special construction is proposed. The error exponent lower bound for the modified decoding algorithm is obtained. Finally, numerical results for the considered error exponent lower bounds are presented and analyzed.
In the paper the usage of low-density parity-check (LDPC) codes to protect storage systems from failures is considered. These codes are the instance of locally recoverable (LRC) codes which obtain much attention during last years regarding storage systems. The system model of distributed storage system is described, with specific types of failures. The coding schemes based on Reed- Solomon (RS) and LDPC codes are formulated for this model taking into account the specific failures types. These coding schemes are compared using several examples of model parameters. The redundancy and locality provided by different coding schemes are estimated. © Springer International Publishing Switzerland 2015.
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.