1. Matrix fraction descriptions in convolutional coding
- Author
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Fornasini, Ettore and Pinto, Raquel
- Subjects
- *
MATRICES (Mathematics) , *POLYNOMIALS , *APPROXIMATION theory , *MATHEMATICS - Abstract
In this paper, polynomial matrix fraction descriptions (MFDs) are used as a tool for investigating the structure of a (linear) convolutional code and the family of its encoders and syndrome formers. As static feedback and precompensation allow to obtain all minimal encoders (in particular, polynomial encoders and decoupled encoders) of a given code, a simple parametrization of their MFDs is provided. All minimal syndrome formers, by a duality argument, are obtained by resorting to output injection and postcompensation. Decoupled encoders are finally discussed as well as the possibility of representing a convolutional code as a direct sum of smaller ones. [Copyright &y& Elsevier]
- Published
- 2004
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