IASTED, International Conference on Intelligent Systems and Control, November 2001
Cited by
Year 2015 : 2 citations
Nonlinear Electronic/Photonic Component Modeling Using Adjoint State-Space Dynamic Neural Network Technique
SA Sadrossadat, P Gunupudi… - … , IEEE Transactions on, 2015 - ieeexplore.ieee.org
Abstract—In this paper, an adjoint state-space dynamic neural network method for modeling
nonlinear circuits and components is presented. This method is used for modeling the
transient behavior of the nonlinear electronic and photonic components. The proposed ...
[PDF] Sensitivity-Analysis-Based Adjoint Neural Network Techniques for Nonlinear Applications
SA Sadrossadat - 2015 - curve.carleton.ca
Abstract Artificial neural networks (ANN) have recently emerged as a powerful
computeraided design (CAD) tool for modeling nonlinear devices and circuits. The overall
objective of this thesis is to develop sensitivity analysis based neural network techniques ...
Year 2007 : 1 citations
Online DGPS Correction Prediction using Recurrent Neural Networks with Unscented Kalman filter
Y Geng - 2007 - gmat.unsw.edu.au
Year 2006 : 1 citations
State-space dynamic neural network technique for high-speed IC applications: modeling and stability ?
Y Cao, R Ding, QJ Zhang - IEEE Transactions on Microwave Theory and Techniques, 2006 - ieeexplore.ieee.org
Year 2005 : 6 citations
Online DGPS Correction Prediction using Recurrent Neural Networks with Unscented Kalman filter
Y Geng - 2007 - gmat.unsw.edu.au
¹ÿ¼ü´ÿ: ¿¨¶ûÿüÿÿ²¨ ͳ¼ÿÏÿÐÿ»¯ Sigma µã ¹ÿ¼ÿ
¸µ½¨¹ú£¬ ÍõТͨ£¬ ½ðÁ¼°²£¬ ÿíÿ° - ϵͳ¹¤³ÿÿëµçÿÿ¼¼ÿõ, 2005 - scholar.ilib.cn £ÿ1£ÝGreg W, Bishop G. An introduction to the Kalman filter[R]. Technical
Report TR 95 - 041, Department of Computer Science, University of North Carolina
at Chapel Hill, Updated, 2003. 1 - 16. £ÿ2£ÝKushner H J. Dynamical ...
