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Correction

A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression. Appl. Sci. 2017, 7, 1106

1
Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
HiSIM Research Center, Hiroshima University, Hiroshima 739-8530, Japan
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2019, 9(7), 1377; https://doi.org/10.3390/app9071377
Submission received: 6 March 2019 / Accepted: 6 March 2019 / Published: 1 April 2019
We, the authors, wish to make the following corrections to our published paper [1].
  • Add the names of Dai Suzuki and Hans Jürgen Mattausch at the second and the last position of the author list, respectively.
  • In the Acknowledgement Section, we omitted adding the following information: “This work was supported by Hiroshima University TAOYAKA Program for creating a flexible, enduring, peaceful society, funded by the Program for Leading Graduated Schools, Ministry of Education, Culture, Sports, Science and Technology”.
  • Add the contribution descriptions of Dai Suzuki and Hans Jürgen Mattausch in the Author Contributions Section as “The design was conceived by Zunkai Huang, Dai Suzuki, Fengwei An, and Hans Jürgen Mattausch. Dai Suzuki carried out initial designs and corresponding experiments”.
  • Add the following references and update the other reference numbers accordingly.
  • 15. Huang, Z.; Zhang, X.; Lei, C.; Zhu, Y.; An, F.; Hui, W.; Feng, S. A vector-quantization compression circuit with on-chip learning ability for high-speed image sensor. IEEE Access 2017, 5, 22132–22143, doi:10.1109/ACCESS.2017.2762399.
The authors would like to apologize for any inconvenience caused. These changes do not affect the scientific conclusions. The manuscript will be updated and the original will remain online on the article webpage with a reference to this Correction.

References

  1. Huang, Z.; Zhang, X.; Chen, L.; Zhu, Y.; An, F.; Wang, H.; Feng, S. A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression. Appl. Sci. 2017, 7, 1106. [Google Scholar] [CrossRef]

Share and Cite

MDPI and ACS Style

Huang, Z.; Suzuki, D.; Zhang, X.; Chen, L.; Zhu, Y.; An, F.; Wang, H.; Feng, S.; Mattausch, H.J. A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression. Appl. Sci. 2017, 7, 1106. Appl. Sci. 2019, 9, 1377. https://doi.org/10.3390/app9071377

AMA Style

Huang Z, Suzuki D, Zhang X, Chen L, Zhu Y, An F, Wang H, Feng S, Mattausch HJ. A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression. Appl. Sci. 2017, 7, 1106. Applied Sciences. 2019; 9(7):1377. https://doi.org/10.3390/app9071377

Chicago/Turabian Style

Huang, Zunkai, Dai Suzuki, Xiangyu Zhang, Lei Chen, Yongxin Zhu, Fengwei An, Hui Wang, Songlin Feng, and Hans Jürgen Mattausch. 2019. "A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression. Appl. Sci. 2017, 7, 1106" Applied Sciences 9, no. 7: 1377. https://doi.org/10.3390/app9071377

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