第12期 全丽萍等：多分辨率小波极限学习机 ·1719· Cao J,Lin Z,HuangG B.Composite function wavelet neural net- 538 works with extreme learning machine.Neurocomputing,2010,73 ]Wang JG,Yang J H,Yun H B,et al.Improved particle swarm (7):1405 optimized back propagation neural network and its application to B]Cao J,Lin Z,Huang G B.Composite function wavelet neural net- production quality modeling.J Univ Sci Technol Beijing,2008,30 works with differential evolution and extreme leamning machine. (10):1188 Neural Process Lett,2011,33(3)251 (王建国，阳建宏，云海滨，等。改进粒子群优化神经网络及 4]Huang G B,Zhou H,Ding X,et al.Extreme learning machine 其在产品质量建模中的应用.北京科技大学学报，2008,30 for regression and multiclass classification.IEEE Trans Syst Man (10):1188) Cbem,2012,42(2):513 [10]Khan A,Yang J,Wu W.Double parallel feedforward neural net- [5]Feng G,Huang G B,Lin Q,et al.Error minimized extreme work based on extreme learning machine with Li regularizer learning machine with growth of hidden nodes and incremental Neurocomputing,2014,128:113 learning.IEEE Trans Neural Netucorks,2009,20(8):1352 [11]Huang J C,Xiao J.Cloud model based on wavelet neural net- [6]Xu C,Li M.Zhang WQ,et al.Post-tcarelet and Variational The- works.Control Theory Appl,2011,28(1):53 ory and Their Application in Image Completion.Beijing:Science (黄景春，肖建.基于小波神经网络的云模型.控制理论与 Press,2013 应用，2011,28(1)：53) (徐晨，李敏，张维强，等.后小波与变分理论及其在图像修 [12]Huang G B.Zhu Q Y,Siew C K.Extreme learning machine: 复中的应用.北京：科学出版社，2013) theory and applications.Neurocomputing,2006,0(1):489 Yang S Y,Jiao LC,Wang M.A new directional multi-esolution [13]Bache K,Lichman M.UCI Machine Learning Repository [R/ ridgelet network.J Xidian Univ,2006,33(4):557 OL.Irvine,CA:School of Information and Computer Science, (杨淑媛，焦李成，王敏.一种新的方向多分辨脊波网络.西 University of California.[2014-05-24].http://archive.ics. 安电子科技大学学报，2006,33(4)：557) uci.edu/ml Sun F.He M.Gao Q.A hybrid algorithm for training adaptive [14]Torgo L.Lus Torgo:Regression Data Sets [DB/OL].014- ridgelet neural network /2011 IEEE International Conference on 05-4].http://www.dec.fe.up.pt/~ltorgo/Regression/Data- Computer Science and Automation Engineering (CSAE),2011: Sets.html第 12 期 全丽萍等: 多分辨率小波极限学习机 ［2］ Cao J，Lin Z，Huang G B． Composite function wavelet neural net￾works with extreme learning machine． Neurocomputing，2010，73 ( 7) : 1405 ［3］ Cao J，Lin Z，Huang G B． Composite function wavelet neural net￾works with differential evolution and extreme learning machine． Neural Process Lett，2011，33( 3) : 251 ［4］ Huang G B，Zhou H，Ding X，et al． Extreme learning machine for regression and multiclass classification． IEEE Trans Syst Man Cybern，2012，42( 2) : 513 ［5］ Feng G，Huang G B，Lin Q，et al． Error minimized extreme learning machine with growth of hidden nodes and incremental learning． IEEE Trans Neural Networks，2009，20( 8) : 1352 ［6］ Xu C，Li M，Zhang W Q，et al． Post-wavelet and Variational The￾ory and Their Application in Image Completion． Beijing: Science Press，2013 ( 徐晨，李敏，张维强，等． 后小波与变分理论及其在图像修 复中的应用． 北京: 科学出版社，2013) ［7］ Yang S Y，Jiao L C，Wang M． A new directional multi-resolution ridgelet network． J Xidian Univ，2006，33( 4) : 557 ( 杨淑媛，焦李成，王敏． 一种新的方向多分辨脊波网络． 西 安电子科技大学学报，2006，33( 4) : 557) ［8］ Sun F，He M，Gao Q． A hybrid algorithm for training adaptive ridgelet neural network / / 2011 IEEE International Conference on Computer Science and Automation Engineering ( CSAE) ，2011: 538 ［9］ Wang J G，Yang J H，Yun H B，et al． Improved particle swarm optimized back propagation neural network and its application to production quality modeling． J Univ Sci Technol Beijing，2008，30 ( 10) : 1188 ( 王建国，阳建宏，云海滨，等． 改进粒子群优化神经网络及 其在产品质量建模中的应用． 北京科技大学学报，2008，30 ( 10) : 1188) ［10］ Khan A，Yang J，Wu W． Double parallel feedforward neural net￾work based on extreme learning machine with L1 /2 regularizer． Neurocomputing，2014，128: 113 ［11］ Huang J C，Xiao J． Cloud model based on wavelet neural net￾works． Control Theory Appl，2011，28( 1) : 53 ( 黄景春，肖建． 基于小波神经网络的云模型． 控制理论与 应用，2011，28( 1) : 53) ［12］ Huang G B，Zhu Q Y，Siew C K． Extreme learning machine: theory and applications． Neurocomputing，2006，70( 1) : 489 ［13］ Bache K，Lichman M． UCI Machine Learning Ｒepository ［Ｒ / OL］． Irvine，CA: School of Information and Computer Science， University of California． ［2014--05--24］． http: / /archive． ics． uci． edu /ml ［14］ Torgo L． Lus Torgo: Ｒegression Data Sets ［DB /OL］． ［2014-- 05--24］． http: / /www． dcc． fc． up． pt / ～ ltorgo /Ｒegression /Data￾Sets． html · 9171 ·