State space and polynomial matrix parametrization of minimal convolutional encoders | IEEE Conference Publication | IEEE Xplore

State space and polynomial matrix parametrization of minimal convolutional encoders


Abstract:

The paper discusses the possibility of characterizing some important properties of convolutional codes and its encoders and syndrome formers by means of matrix fraction d...Show More

Abstract:

The paper discusses the possibility of characterizing some important properties of convolutional codes and its encoders and syndrome formers by means of matrix fraction descriptions and state space models. A complete parametrization is then provided for all minimal encoders and minimal syndrome formers of a given code. Finally state feedback and static precompensation (resp.output injection and postcompensation) allow to synthesize all minimal encoders (resp. minimal syndrome formers), when a minimal one is available.
Date of Conference: 04-07 September 2001
Date Added to IEEE Xplore: 27 April 2015
Print ISBN:978-3-9524173-6-2
Conference Location: Porto, Portugal

References

References is not available for this document.