In this paper we introduce a new type of superregular matrices that give rise to novel constructions of two-dimensional (2D) convolutional codes with finite support. These codes are of rate 1=n and degree d with n d +1 and achieve the maximum possible distance among all 2D convolutional codes with finite support with the same parameters
Superregular matrices are a type of lower triangular Toeplitz matrix that arises in the context of c...
AbstractThis article focuses on the characterization of two models of concatenated convolutional cod...
In recent times the 2D system analysis has constituted a stimulating research topic, both for the th...
Maximum distance separable convolutional codes are the codes that present best performance in error ...
Maximum distance separable (MDS) block codes and MDS 1D convolutional codes are the most robust code...
Maximum distance separable (MDS) block codes and MDS 1D convolutional codes are the most robust code...
This paper deals with the problem of constructing superregular matrices that lead to MDP convolutio...
In this paper, two-dimensional convolutional codes constituted by sequences in where is a finite fie...
The minimum distance of a code is an important measure of robustness of the code since it provides a...
In this paper we address the problem of extending the well-known notion of column distance of one-di...
The main results of this paper are twofold: the first one is a matrix theoretical result. We say that...
Maximum distance separable convolutional codes are the codes that present best performance in error ...
Two-dimensional convolutional codes are considered, with codewords having compact support indexed in...
In this paper, we investigate the properties of two-dimensional (2D) convolutional codes which are o...
Algebraic methods for the design of series of maximum distance separable (MDS) linear block and conv...
Superregular matrices are a type of lower triangular Toeplitz matrix that arises in the context of c...
AbstractThis article focuses on the characterization of two models of concatenated convolutional cod...
In recent times the 2D system analysis has constituted a stimulating research topic, both for the th...
Maximum distance separable convolutional codes are the codes that present best performance in error ...
Maximum distance separable (MDS) block codes and MDS 1D convolutional codes are the most robust code...
Maximum distance separable (MDS) block codes and MDS 1D convolutional codes are the most robust code...
This paper deals with the problem of constructing superregular matrices that lead to MDP convolutio...
In this paper, two-dimensional convolutional codes constituted by sequences in where is a finite fie...
The minimum distance of a code is an important measure of robustness of the code since it provides a...
In this paper we address the problem of extending the well-known notion of column distance of one-di...
The main results of this paper are twofold: the first one is a matrix theoretical result. We say that...
Maximum distance separable convolutional codes are the codes that present best performance in error ...
Two-dimensional convolutional codes are considered, with codewords having compact support indexed in...
In this paper, we investigate the properties of two-dimensional (2D) convolutional codes which are o...
Algebraic methods for the design of series of maximum distance separable (MDS) linear block and conv...
Superregular matrices are a type of lower triangular Toeplitz matrix that arises in the context of c...
AbstractThis article focuses on the characterization of two models of concatenated convolutional cod...
In recent times the 2D system analysis has constituted a stimulating research topic, both for the th...