Evaluation of K-SVD embedded with modified l<inf>1</inf>-norm sparse representation algorithm
MetadataShow full item record
© 2017, Springer Nature Singapore Pte Ltd. The K-SVD algorithm aims to find an adaptive dictionary for a set of signals by using the sparse representation optimization and constrained singular value decomposition. In this paper, firstly, the original K-SVD algorithm, as well as some sparse representation algorithms including l 0 -norm OMP and l 1 -norm Lasso were reviewed. Secondly, the revised Lasso algorithm was embedded into the K-SVD process and a new different K-SVD algorithms with l 1 -norm Lasso embedded in (RL-K-SVD algrithm) was established. Finally, extensive experiments had been completed on necessary parameters determination, further on the performance compare of recovery error and recognition for the original K-SVD and RL-K-SVD algorithms. The results indicate that within a certain scope of parameter settings, the RL-K-SVD algorithm performs better on image recognition than K-SVD; the time cost for training sample number is lower for RL-K-SVD in case that the sample number is increased to a certain extend.
Showing items related by title, author, creator and subject.
Zhang, X.; Pham, DucSon; Venkatesh, S.; Liu, Wan-Quan; Phung, D. (2015)Face recognition with multiple views is a challenging research problem. Most of the existing works have focused on extracting shared information among multiple views to improve recognition. However, when the pose variation ...
Liu, J.; Zhou, W.; Juwono, Filbert Hilman; Huang, D. (2017)© 2017 Elsevier B.V. In this paper, a reweighted smoothed l0-norm algorithm is proposed for direction-of-arrival (DOA) estimation in monostatic multiple-input multiple-output (MIMO) radar. The proposed method firstly ...
Liu, J.; Zhou, W.; Juwono, Filbert Hilman (2017)© 2017 by the authors. Licensee MDPI, Basel, Switzerland. Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation ...