Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low- - Info and Reading Options
"Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-" was published by Independently Published in 2018, the book is classified in Science genre, it has 26 pages and the language of the book is English.
“Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-” Metadata:
- Title: ➤ Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-
- Language: English
- Number of Pages: 26
- Is Family Friendly: Yes - No Mature Content
- Publisher: Independently Published
- Publish Date: 2018
- Genres: Science
Edition Specifications:
- Weight: 0.086
- Pagination: 26
Edition Identifiers:
- Google Books ID: nqo6vQEACAAJ
- The Open Library ID: OL40675177M - OL29558918W
- ISBN-13: 9781728906683
- ISBN-10: 1728906687
- All ISBNs: 9781728906683 - 1728906687
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Lin, Shu and Fossorier, Marc Goddard Space Flight Center NAG5-931; NAG5-2938.
"Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-" Description:
Google Books:
For long linear block codes, maximum likelihood decoding based on full code trellises would be very hard to implement if not impossible. In this case, we may wish to trade error performance for the reduction in decoding complexity. Sub-optimum soft-decision decoding of a linear block code based on a low-weight sub-trellis can be devised to provide an effective trade-off between error performance and decoding complexity. This chapter presents such a suboptimal decoding algorithm for linear block codes. This decoding algorithm is iterative in nature and based on an optimality test. It has the following important features: (1) a simple method to generate a sequence of candidate code-words, one at a time, for test; (2) a sufficient condition for testing a candidate code-word for optimality; and (3) a low-weight sub-trellis search for finding the most likely (ML) code-word. Lin, Shu and Fossorier, Marc Goddard Space Flight Center NAG5-931; NAG5-2938
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