A VLSI architecture for weight perturbation on chip learning implementation
暂无分享,去创建一个
[1] A.H.M. van Roermund,et al. A reduced-area low-power low-voltage single-ended differential pair , 1997 .
[2] Marwan A. Jabri,et al. Weight perturbation: an optimal architecture and learning technique for analog VLSI feedforward and recurrent multilayer networks , 1992, IEEE Trans. Neural Networks.
[3] Ronald S. Gyurcsik,et al. Toward a general-purpose analog VLSI neural network with on-chip learning , 1997, IEEE Trans. Neural Networks.
[4] Daniele D. Caviglia,et al. An experimental analog VLSI neural network with on-chip back-propagation learning , 1992, ESSCIRC '92: Eighteenth European Solid-State Circuits conference.
[5] Daniele D. Caviglia,et al. An analog on-chip learning circuit architecture of the weight perturbation algorithm , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).
[6] Andrzej Cichocki,et al. Neural networks for optimization and signal processing , 1993 .
[7] Daniele D. Caviglia,et al. Analog CMOS current mode neural primitives , 2000, 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353).
[8] Joshua Alspector,et al. A Study of Parallel Perturbative Gradient Descent , 1994, NIPS.
[9] Christofer Toumazou,et al. Analogue IC design : the current-mode approach , 1993 .
[10] Francois Krummenacher,et al. A 4-MHz CMOS Continuous-Time Filter with On-Chip Automatic Tuning , 1987, ESSCIRC '87: 13th European Solid-State Circuits Conference.