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NTIS 바로가기IEEE transactions on components, packaging, and manufacturing technology, v.4 no.8, 2014년, pp.1380 - 1390
Ellis, Charles D. (Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA) , Hamilton, Michael C. (Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA) , Nakamura, James R. (Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA) , Wilamowski, Bogdan M. (Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA)
Determination of copper electroplating additives is critical to ensuring consistent copper plating of conductors and through-silicon-vias used in semiconductor processing and electronics packaging. The present analysis methods require many chemical analysis steps, generate waste, and are not very ac...
Muttil, N., Chau, K.-W.. Neural network and genetic programming for modelling coastal algal blooms. International journal of environment and pollution, vol.28, no.3, 223-238.
Wu, C. L., Chau, K. W., Li, Y. S.. Predicting monthly streamflow using data‐driven models coupled with data‐preprocessing techniques. Water resources research, vol.45, no.8, 2007WR006737-.
Long-Term Prediction of Discharges in Manwan Reservoir Using Artificial Neural Network Models (Computer Science) cheng 2005 3 1040
Chau, K.W.. Application of a PSO-based neural network in analysis of outcomes of construction claims. Automation in construction, vol.16, no.5, 642-646.
Rumelhart, David E., Hinton, Geoffrey E., Williams, Ronald J.. Learning representations by back-propagating errors. Nature, vol.323, no.6088, 533-536.
Wilamowski, B.M., Cotton, N.J., Kaynak, O., Dundar, G.. Computing Gradient Vector and Jacobian Matrix in Arbitrarily Connected Neural Networks. IEEE transactions on industrial electronics : a publication of the IEEE Industrial Electronics Society, vol.55, no.10, 3784-3790.
Ampazis, N., Perantonis, S.J.. Two highly efficient second-order algorithms for training feedforward networks. IEEE transactions on neural networks, vol.13, no.5, 1064-1074.
IEEE Trans Neural Netw Training two-layered feedforward networks with variable projection method kim 2008 10.1109/TNN.2007.911739 19 371
Wilamowski, B.M.. Neural network architectures and learning algorithms. IEEE industrial electronics magazine, vol.3, no.4, 56-63.
PCB News Mag Electrolytic copper bath analysis for PCB fabrication lefebvre 2010
Huang, G.B., Chen, L.. Enhanced random search based incremental extreme learning machine. Neurocomputing, vol.71, no.16, 3460-3468.
Proc Int Symp Electrochem Soc Meeting Electrochemical processing in ULSI and MEMS deligianni 2005 45
Huang, Guang-Bin, Chen, Lei. Convex incremental extreme learning machine. Neurocomputing, vol.70, no.16, 3056-3062.
Plating and Surface Finishing Determination of the individual components in acid copper plating baths freitag 1983 70 55
Proc 70th Amer Electroplaters Soc Tech Conf Plating bath analysis and control by CVS gluzman 1983 13
Wilamowski, B M, Hao Yu. Neural Network Learning Without Backpropagation. IEEE transactions on neural networks, vol.21, no.11, 1793-1803.
Solid State Technol Optimized bath control for void-free copper deposition sun 2001 44 46
Determination of leveler in acid copper baths by response curve technique 0
Fundamentals of Cyclic Voltammetric Stripping 2014
West, Alan C.. Theory of Filling of High-Aspect Ratio Trenches and Vias in Presence of Additives. Journal of the Electrochemical Society : JES, vol.147, no.1, 227-.
Taormina, R., Chau, K.w., Sethi, R.. Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon. Engineering applications of artificial intelligence, vol.25, no.8, 1670-1676.
Ferrari, Silvia, Jensenius, Mark. A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training. IEEE transactions on neural networks, vol.19, no.6, 996-1009.
Phansalkar, V.V., Sastry, P.S.. Analysis of the back-propagation algorithm with momentum. IEEE transactions on neural networks, vol.5, no.3, 505-506.
Qing Song, Spall, J.C., Yeng Chai Soh, Jie Ni. Robust Neural Network Tracking Controller Using Simultaneous Perturbation Stochastic Approximation. IEEE transactions on neural networks, vol.19, no.5, 817-835.
The QR Decomposition and Regression 2014
Huang, Guang-Bin, Chen, Lei, Siew, Chee-Kheong. Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE transactions on neural networks, vol.17, no.4, 879-892.
Mangasarian, O.L., Musicant, D.R.. Robust linear and support vector regression. IEEE transactions on pattern analysis and machine intelligence, vol.22, no.9, 950-955.
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