Syndrome decoding of binary rate k/n convolutional codes

J.P.M. Schalkwijk; A.J. Vinck; K.A. Post

doi:10.1109/TIT.1978.1055937

Syndrome decoding of binary rate k/n convolutional codes

J.P.M. Schalkwijk
, A.J. Vinck
, K.A. Post

Mathematics and Computer Science

Research output: Contribution to journal › Article › Academic › peer-review

25 Citations (Scopus)

Abstract

A state-space approach to the syndrome decoding of binary rate k/n convolutional codes is described. State-space symmetries of a certain class of codes can be exploited to obtain a reduction in the exponent of growth of the decoder hardware. Aside from these savings it is felt that the state-space formalism developed has some unique intrinsic value.

Original language	English
Pages (from-to)	553-562
Number of pages	10
Journal	IEEE Transactions on Information Theory
Volume	24
Issue number	5
DOIs	https://doi.org/10.1109/TIT.1978.1055937
Publication status	Published - 1978

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10.1109/TIT.1978.1055937

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title = "Syndrome decoding of binary rate k/n convolutional codes",

abstract = "A state-space approach to the syndrome decoding of binary rate k/n convolutional codes is described. State-space symmetries of a certain class of codes can be exploited to obtain a reduction in the exponent of growth of the decoder hardware. Aside from these savings it is felt that the state-space formalism developed has some unique intrinsic value.",

author = "J.P.M. Schalkwijk and A.J. Vinck and K.A. Post",

year = "1978",

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AU - Vinck, A.J.

AU - Post, K.A.

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AB - A state-space approach to the syndrome decoding of binary rate k/n convolutional codes is described. State-space symmetries of a certain class of codes can be exploited to obtain a reduction in the exponent of growth of the decoder hardware. Aside from these savings it is felt that the state-space formalism developed has some unique intrinsic value.

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DO - 10.1109/TIT.1978.1055937

M3 - Article

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VL - 24

SP - 553

EP - 562

JO - IEEE Transactions on Information Theory

JF - IEEE Transactions on Information Theory

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ER -

Syndrome decoding of binary rate k/n convolutional codes

Abstract

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