Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

book chapter · Communications in computer and information science · 2017

Low-Complexity Soft-Decision Decoder Architecture for BCH Code in the BeiDou System

Chaoyi Zhang, Haiyang Liu, Songlin Ou, Jinhai Li, Jinhai Sun, Yuepeng Yan

Cited by 1Abstract and details only

Abstract

The index has no abstract for this paper. The publisher’s page may have one.

Cite this paper

APA 7

Zhang, C., Liu, H., Ou, S., Li, J., Sun, J., & Yan, Y. (2017). Low-Complexity Soft-Decision Decoder Architecture for BCH Code in the BeiDou System. Communications in computer and information science, 383–391. https://doi.org/10.1007/978-981-10-4211-9_37

MLA 9

Zhang, Chaoyi, et al. “Low-Complexity Soft-Decision Decoder Architecture for BCH Code in the BeiDou System.” Communications in computer and information science, 2017, pp. 383–91, https://doi.org/10.1007/978-981-10-4211-9_37.

Chicago

Zhang, Chaoyi, Haiyang Liu, Songlin Ou, Jinhai Li, Jinhai Sun, and Yuepeng Yan. 2017. “Low-Complexity Soft-Decision Decoder Architecture for BCH Code in the BeiDou System.” Communications in computer and information science: 383–91. https://doi.org/10.1007/978-981-10-4211-9_37.

Harvard

Zhang, C. et al. (2017) ‘Low-Complexity Soft-Decision Decoder Architecture for BCH Code in the BeiDou System’, Communications in computer and information science, pp. 383–391. Available at: https://doi.org/10.1007/978-981-10-4211-9_37.

BibTeX
@incollection{zhang2017complexity,
  title = {{Low-Complexity Soft-Decision Decoder Architecture for BCH Code in the BeiDou System}},
  author = {Zhang, Chaoyi and Liu, Haiyang and Ou, Songlin and Li, Jinhai and Sun, Jinhai and Yan, Yuepeng},
  booktitle = {Communications in computer and information science},
  pages = {383--391},
  year = {2017},
  doi = {10.1007/978-981-10-4211-9_37}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers