JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (5): 157-165.doi: 10.6040/j.issn.1672-3961.0.2017.268
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BAO Tala1,2, MA Jian1,2*, GAN Zuwang1,2
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| [1] SHIM J, KOSTECKI R, RICHARDSON T. Electrochemical analysis for cycle performance and capacity fading of a lithium-ion battery cycled at elevated temperature[J]. Journal of Power Sources, 2002, 112(1):222-230. [2] ZHANG X, ROSSP, KOSTECKI R. Diagnostic characterization of high power lithium-ion batteries for use in hybride lectric vehicles[J].Journal of the Electrochemical Society, 2001, 148(5):A463-A470. [3] LI Y, OMAR N, NANINI-MAURY E, et al. Performance and reliability assessment of NMC lithium ion batteries for stationary application[C] //Processdings of IEEE on Vehicle Power and Propulsion 2016. Hangzhou, China:VPPC, 2016:137. [4] ARULAMPALAM M S, MASKELL S, GORDON N, et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE Transactions on Signal Processing, 2002, 50(2): 174-188. [5] AN D, CHOI J H, KIM N H. Prognostics 101: a tutorial for particle filter-based prognostics algorithm using Matlab[J]. Reliability Engineering & System Safety, 2013, 115: 161-169. [6] 王靖. 流形学习的理论与方法研究[D]. 杭州: 浙江大学, 2006. WANG Jing. Research on manifold learning:theories and approaches[D]. Hangzhou: Zhejiang University, 2006. [7] 曹丽. 基于流形的特征抽取及人脸识别研究[D].扬州:扬州大学, 2009. CAO Li. Manifold-based feature extraction and face recognition analysis[D].Yangzhou:Yangzhou University, 2009. [8] TENENBAUM J B, DE SILVA V, LANGFORD J C. A global geometric framework for nonlinear dimensionality reduction[J]. Science, 2000, 290(5500): 2319-2323. [9] ROWEIS S T, SAUL L K. Nonlinear dimensionality reduction by locally linear embedding[J]. Science, 2000, 290(5500): 2323-2326. [10] BELKIN M, NIYOGI P. Laplacian eigenmaps for dimensionality reduction and data representation[J]. Neural computation, 2003, 15(6): 1373-1396. [11] 李小丽, 薛清福. 几种流形学习算法的比较研究[J]. 电脑与信息技术, 2009,17(3): 14-18. LI Xiaoli, XUE Qingfu. A comparative study of some manifold learning algorithms[J]. Computer and Information Technology, 2009, 17(3):14-18. [12] HE X, NIYOGI P. Locality preserving projections[C] //Proceedings of Neural Information Processing Systems on Computer Science. Carson City, USA: NIPS, 2003:153. [13] GONG M, BO L, WANG L, et al. Image texture classification using a manifold-distance-based evolutionary clustering method[J]. Optical Engineering, 2008, 47(7): 77201-77210. |
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