题 目：Stableimage restoration by TV type methods
内容简介：Somenew TV type minimization models are introduced to investigate robustimage recovery from a certain number of noisy measurements by theproposed TV type minimization models. Error bounds of robust imagerecovery from compressed measurements via the proposed minimizationmodels are established, and the RIP based condition is improvedcompared with total variation (TV) minimization. Numerical results ofimage reconstruction demonstrate our theoretical results andillustrate the efficiency of the proposed TV type minimization modelsamong state of-the-art methods.
报告人：谌稳固
报告人简介：北京应用物理与计算数学研究所研究员，博士生导师，主要从事调和分析、压缩感知、机器学习、大数据分析的理论及应用研究，在IEEETransactions on Information Theory, Applied and ComputationalHarmonic Analysis，InverseProblems, SIAM Journal on Imaging Sciences, Journal of MachineLearning等学术期刊发表科研论文70余篇。
时 间：2023年11月17日（周五）上午9：00开始
地 点：腾讯会议：184-215-195
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