Improved Performance of CDL Algorithm Using DDELM-AE and AK-SVD
Due to the poor robustness and high complexity of the concentrated dictionary learning (CDL) algorithm, this paper addresses these issues using denoising deep extreme learning machine based on autoencoder (DDELM-AE) and approximate k singular value decomposition (AK-SVD). Different from the CDL algorithm, on input, DDELM-AE is added for enhancing denoising ability and AK-SVD replaces K-SVD for improving running speed. Additionally, experimental results show that the improved algorithm is more efficient than the original CDL algorithm in terms of running time, denoising ability, and stability.
KeywordsSignal compression CDL Deep learning DDELM-AE AK-SVD
This work is supported by Natural Science Foundation of China (Grant No. 61702066), Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No. KJ1704080), and Chongqing Research Program of Basic Research and Frontier Technology (Grant No. cstc2017jcyjAX0256).
- 1.Aharon M, Elad M, Bruckstein A. K-SVD: design of dictionaries for sparse representation. In: Proceedings of the workshop on signal processing with adaptive sparse structured representations (SPARS05); 2005. p. 9–12.Google Scholar
- 3.Wei F, Shutao L, Leyuan F, Benediktsson JA. Contextual online dictionary learning for hyperspectral image classification. IEEE Trans Geosci Remote Sens. 2017;1–12.Google Scholar
- 4.Gkioulekas IA, Zickler T. Dimensionality reduction using the sparse linear model. In: Proceedings of the 2011 advances in neural information processing systems; 2011. p. 271–9.Google Scholar
- 5.Calderbank R, Jafarpour S, Schapire R. Compressed learning: universal sparse dimensionality reduction and learning in the measurement domain. Princeton University, USA; 2009. Technical Report.Google Scholar
- 7.SiLong Z, YuanXiang L, Xian W, XiShuai P. Nonlinear dimensionality reduction based on dictionary learning. In: ACTA AUTOMATICA SINICA; 2016. p. 1065–76.Google Scholar
- 9.Shuting C, Shaojia W, Binling L, Daolin H, Simin Y, Shuqiong X. A dictionary-learning algorithm based on method of optimal directions and approximate K-SVD. In: 2016 35th Chinese control conference (CCC); 2016. p. 6957–61.Google Scholar
- 10.Zeyde R, Elad M, Protter M. On single image scale-upusingsparse-representations. In: Proceedings of the 7th international conference on curves and surfaces; 2012. p. 711–30.Google Scholar