
The free distance of a convolutional code is a reliable indicator of its performance. However its computation is not an easy task. In this paper, we present some algorithms to compute the free distance with good efficiency that work for convolutional codes of all rates and over any field. Furthermore we discuss why an algorithm which is claimed to be very efficient is incorrect.
10123 Institute of Mathematics, Free distance, 510 Mathematics, 2604 Applied Mathematics, Computer Science - Information Theory, Convolutional codes, 2614 Theoretical Computer Science, 1710 Information Systems, 2611 Modeling and Simulation
10123 Institute of Mathematics, Free distance, 510 Mathematics, 2604 Applied Mathematics, Computer Science - Information Theory, Convolutional codes, 2614 Theoretical Computer Science, 1710 Information Systems, 2611 Modeling and Simulation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
