报告题目：A subfield-based construction of optimal linear codes over finite fields
报告摘要：Linear codes have a wide range of applications in the data storage systems, communication systems and consumer electronics products. In this talk, we present four families of linear codes over finite fields from the complements of either the union of subfields or the union of cosets of a subfield, which can produce infinite families of optimal linear codes, including infinite families of (near) Griesmer codes. We characterize the optimality of these four families of linear codes with an explicit computable criterion using the Griesmer bound and obtain many distance optimal linear codes. In addition, by a more in-depth discussion on some special cases of these four families of linear codes, we obtain several classes of (distance) optimal linear codes with few weights and completely determine their weight distributions. We also show that most of our linear codes are self-orthogonal or minimal which are useful in applications.
报告时间：2022年11月15日14:30
报告地点：腾讯会议号196 722 571
邀 请 人：杜小妮 教授
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报告人简介
李念，湖北大学教授，博士生导师。2013年于西南交通大学获博士学位，导师唐小虎教授；博士期间在挪威卑尔根大学联合培养两年，导师Tor Helleseth院士；随后三年先后于香港科技大学和挪威卑尔根大学继续从事关于代数编码与密码方面的博士后和研究员工作，合作导师为熊茂胜和Lilya Budaghyan教授。主要研究密码、编码及其相关的数学理论。近年来在密码函数、线性码、序列设计等领域做出了⼀系列成果，主持国家自然科学基金2项、湖北省杰青等省部级基金3项，代表性成果发表在国内外重要学术期刊《IEEE Transactions on Information Theory》、《Designs, Codes and Cryptography》和《Finite Fields and Their Applications》等上。2017年和2019年分别入选湖北省楚天学者计划和湖北省百人计划。
