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New Families of p-Ary Sequences from Quadratic Form with Low Correlation and Large Linear Span

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Sequences and Their Applications - SETA 2004 (SETA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3486))

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Abstract

The quadratic form technique has many applications in sequence design including determining certain exponential sums. A key idea in this technique is to transform the problem of computing exponential sums into determining the weights of certain quadratic forms. We use this idea to define two new families of non-binary sequences and determine their correlation properties. The new families of sequences possess low correlation and large linear complexity properties.

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Author information

Authors and Affiliations

  1. Institute of Mobile Communications, Southwest Jiaotong University, Chengdu, China

    Xiaohu Tang & Pingzhi Fan

  2. Department of Computer Science and Software Engineering, University of Melbourne, VIC, 3010, Australia

    Parampalli Udaya

Authors
  1. Xiaohu Tang
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  2. Parampalli Udaya
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  3. Pingzhi Fan
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Editor information

Editors and Affiliations

  1. Department of Informatics, University of Bergen, PB 7803, 5020, Bergen, Norway

    Tor Helleseth

  2. University of Ilinois at Urbana-Champaign, 1406 West Green Street, IL 61801, Urbana, USA

    Dilip Sarwate

  3. Department of Electrical and Electronic Engineering, Yonsei University, 121-749, Seoul, Korea

    Hong-Yeop Song

  4. Dept. of Electronics and Electrical Engineering, Pohang University of Science and Technology (POSTECH), 790-784, Pohang, Kyungbuk, Korea

    Kyeongcheol Yang

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© 2005 Springer-Verlag Berlin Heidelberg

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Tang, X., Udaya, P., Fan, P. (2005). New Families of p-Ary Sequences from Quadratic Form with Low Correlation and Large Linear Span. In: Helleseth, T., Sarwate, D., Song, HY., Yang, K. (eds) Sequences and Their Applications - SETA 2004. SETA 2004. Lecture Notes in Computer Science, vol 3486. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11423461_18

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  • DOI: https://doi.org/10.1007/11423461_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26084-4

  • Online ISBN: 978-3-540-32048-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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