Qiao Jun-Fei, Bo Ying-Chun, Han Guang. Application of ESN-based multi indices dual heuristic dynamic programming on wastewater treatment process. Acta Automatica Sinica, 2013, 39(7): 1146-1151 (乔俊飞, 薄迎春, 韩广. 基于ESN的多指标DHP控制策略在污水处理过程中的应用. 自动化学报, 2013, 39(7): 1146-1151)
[2]
Li G Q, Niu P F, Zhang W P, Zhang Y. Control of discrete chaotic systems based on echo state network modeling with an adaptive noise canceler. Knowledge-Based Systems, 2012, 35: 35-40
[3]
Peng Yu, Wang Jian-Min, Peng Xi-Yuan. Researches on time series prediction with echo state networks. Acta Electronica Sinica, 2010, 38(2A): 148-154 (彭宇, 王建民, 彭喜元. 基于回声状态网络的时间序列预测方法研究. 电子学报, 2010, 38(2A): 148-154)
[4]
Dutoit X, Schrauwen B, Van Campenhout J, Stroobandt D, Van Brussel H, Nuttin M. Pruning and regularization in reservoir computing. Neurocomputing, 2009, 72(7-9): 1534-1546
[5]
Kump P, Bai E W, Chan K S, Eichinger B, Li K. Variable selection via RIVAL (removing irrelevant variables amidst LASSO iterations) and its application to nuclear material detection. Automatica, 2012, 48(9): 2107-2115
[6]
Han Min, Li De-Cai. An norm 1 regularization term ELM algorithm based on surrogate function and Bayesian framework. Acta Automatica Sinica, 2011, 37(11): 1344-1350 (韩敏, 李德才. 基于替代函数及贝叶斯框架的1范数ELM算法. 自动化学报, 2011, 37(11): 1344-1350)
[7]
Tibshirani R. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B (Methodological), 1996, 58(1): 267-288
[8]
Efron B, Hastie T, Johnstone I, Tibshirani R. Least angle regression. The Annals of Statistics, 2004, 32(2): 407-499
[9]
Watanabe S. A widely applicable Bayesian information criterion. Journal of Machine Learning Research, 2013, 14(1): 867-897
[10]
Jaeger H, Hass H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science, 2004, 304(5667): 78-80
[11]
Ongenae F, Van Looy S, Verstraeten D, Verplancke T, Benoit D, De Turck F, Dhaene T, Schrauwen B, Decruyenaere J. Time series classification for the prediction of dialysis in critically ill patients using echo state networks. Engineering Applications of Artificial Intelligence, 2013, 26(3): 984-996
[12]
Lukosevicius M, Jaeger H. Reservoir computing approaches to recurrent neural network training. Computer Science Review, 2009, 3(3): 127-149
[13]
Rong H J, Ong Y S, Tan A H, Zhu Z. A fast pruned-extreme learning machine for classification problem. Neurocomputing, 2008, 72(1-3): 359-366
[14]
Miche Y, Sorjamaa A, Bas P, Simula O, Jutten C, Lendasse A. OP-ELM: optimally pruned extreme learning machine. IEEE Transactions on Neural Networks, 2010, 21(1): 158-162
Liu Jian-Wei, Li Shuang-Cheng, Luo Xiong-Lin. Classification algorithm of support vector machine via p-norm regularization. Acta Automatica Sinica, 2012, 38(1): 76-87 (刘建伟, 李双成, 罗雄麟. p范数正则化支持向量机分类算法. 自动化学报, 2012, 38(1): 76-87)
[17]
Miche Y, Van Heeswijk M, Bas P, Simula O, Lendasse A. TROP-ELM: a double-regularized ELM using LARS and Tikhonov regularization. Neurocomputing, 2011, 74(16): 2413-2421
[18]
Friedman J H. Fast sparse regression and classification. International Journal of Forecasting, 2012, 28(3): 722-738
[19]
Peng Yi-Gang, Suo Jin-Li, Dai Qiong-Hai, Xu Wen-Li. From compressed sensing to low-rank matrix recovery: theory and applications. Acta Automatica Sinica, 2013, 39(7): 981-994(彭义刚, 索津莉, 戴琼海, 徐文立. 从压缩传感到低秩矩阵恢复: 理论与应用. 自动化学报, 2013, 39(7): 981-994)
[20]
Stoica P, Selen Y. Model-order selection: a review of information criterion rules. IEEE Signal Processing Magazine, 2004, 21(4): 36-47
[21]
Wu C L, Chau K W. Prediction of rainfall time series using modular soft computing methods. Engineering Applications of Artificial Intelligence, 2013, 26(3): 997-1007
[22]
Box G E P, Jenkins G M, Reinsel G C. Time Series Analysis: Forecasting and Control. New Jersey, USA: John Wiley & Sons, 2008. 677-678