文件名称:lecture-notes
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《压缩感知与稀疏恢复》课程是 Justin Romberg教授访问清华大学期间讲授的短期课程。该资料为其讲课的课件。-"Compressed sensing and sparse recovery" is taught during the visit Tsinghua University professor Justin Romberg short courses. The data for lectures courseware.
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下载文件列表
lecture notes/01-basis-expansion-fundamentals.pdf
lecture notes/02-overview-of-sparsity-theory-and-applications.pdf
lecture notes/03-sparse-approx-algorithms.pdf
lecture notes/04-uncertainty-principles-for-unions-of-bases.pdf
lecture notes/05-overview-of-compressive-sensing.pdf
lecture notes/06-l1-minimization-duality-and-optimality.pdf
lecture notes/07-l1-recovery-with-the-restricted-isometry-property.pdf
lecture notes/08-stability-of-L1-recovery.pdf
lecture notes/09-the-RIP-for-Gaussian-matrices.pdf
lecture notes/10-low-rank-recovery-and-bilinear-problems.pdf
lecture notes/11-dynamic-l1-recovery.pdf
lecture notes
lecture notes/02-overview-of-sparsity-theory-and-applications.pdf
lecture notes/03-sparse-approx-algorithms.pdf
lecture notes/04-uncertainty-principles-for-unions-of-bases.pdf
lecture notes/05-overview-of-compressive-sensing.pdf
lecture notes/06-l1-minimization-duality-and-optimality.pdf
lecture notes/07-l1-recovery-with-the-restricted-isometry-property.pdf
lecture notes/08-stability-of-L1-recovery.pdf
lecture notes/09-the-RIP-for-Gaussian-matrices.pdf
lecture notes/10-low-rank-recovery-and-bilinear-problems.pdf
lecture notes/11-dynamic-l1-recovery.pdf
lecture notes
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