The K-SVD is a new algorithm for training dictionaries for linear representation of signals. Given a set of signals, the K-SVD tries to extract the best dictionary that can sparsely represent those signals. Thorough discussion concerning the K-SVD a
文章目录论文问题描述求解原理python 实现KSVD 算法测试结果可视化函数
论文
M. Aharon, M. Elad and A. Bruckstein, “K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation,” in IEEE Transactions on Signal Processing, vol. 54, no. 11, pp. 4311-4322, Nov.
