Title :
A New Training Algorithm for Diagonal Recurrent Neural Network Based on Particle Filter
Author :
Xiaolong, Deng ; Pingfang, Xhou
Author_Institution :
Dept. of Mech. Eng., Jiangsu Coll. of Inf. Technol., Wuxi, China
Abstract :
Based on particle filter, a new training algorithm combining the extended Kalman filter (EKF) for neural network is presented. The new algorithm is firstly applied to train diagonal recurrent neural network (DRNN). A method to evaluate the dynamical performance of DRNN is introduced. Network weights of particles are optimized by the resampling algorithm. Simulation results of the nonlinear dynamical identification verify the validity of the new algorithm.
Keywords :
Kalman filters; learning (artificial intelligence); nonlinear filters; recurrent neural nets; diagonal recurrent neural network; extended Kalman filter; network weights; nonlinear dynamical identification; particle filter; resampling algorithm; training algorithm; Computational intelligence; Computer networks; Educational institutions; Information technology; Mechanical engineering; Neural networks; Neurons; Nonlinear dynamical systems; Particle filters; Recurrent neural networks; EKF; diagonal recurrent neural network; nonlinear identification; particle filter;
Conference_Titel :
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3645-3
DOI :
10.1109/CINC.2009.174
