Relaxed conditions for convergence analysis of online back-propagation algorithm with L2 regularizer for Sigma-Pi-Sigma neural network
暂无分享,去创建一个
Yan Liu | Chao Zhang | Dakun Yang | Chao Zhang | Dakun Yang | Yan Liu
[1] Zongben Xu,et al. Essential rate for approximation by spherical neural networks , 2011, Neural Networks.
[2] Wei Wu,et al. A modified gradient learning algorithm with smoothing L1/2 regularization for Takagi-Sugeno fuzzy models , 2014, Neurocomputing.
[3] Lixiang Li,et al. Stochastic synchronization of complex network via a novel adaptive nonlinear controller , 2014 .
[4] H. White. Some Asymptotic Results for Learning in Single Hidden-Layer Feedforward Network Models , 1989 .
[5] Wei Wu,et al. Convergence Analysis of Batch Gradient Algorithm for Three Classes of Sigma-Pi Neural Networks , 2007, Neural Processing Letters.
[6] Chien-Kuo Li. A Sigma-Pi-Sigma Neural Network (SPSNN) , 2004, Neural Processing Letters.
[7] Xin Li,et al. Training Multilayer Perceptrons Via Minimization of Sum of Ridge Functions , 2002, Adv. Comput. Math..
[8] Wei Wu,et al. Boundedness and Convergence of Online Gradient Method with Penalty for Linear Output Feedforward Neural Networks , 2009, Neural Processing Letters.
[9] Ashraf M. Abdelbar,et al. Advanced learning methods and exponent regularization applied to a high order neural network , 2014, Neural Computing and Applications.
[10] Wei Wu,et al. Boundedness and Convergence of Online Gradient Method With Penalty for Feedforward Neural Networks , 2009, IEEE Transactions on Neural Networks.
[11] Pascal Bianchi,et al. Convergence of a Multi-Agent Projected Stochastic Gradient Algorithm for Non-Convex Optimization , 2011, IEEE Transactions on Automatic Control.
[12] Russell Reed,et al. Pruning algorithms-a survey , 1993, IEEE Trans. Neural Networks.
[13] Ovidiu Radulescu,et al. Convergence of stochastic gene networks to hybrid piecewise deterministic processes , 2011, 1101.1431.
[14] Lennart Ljung,et al. Analysis of recursive stochastic algorithms , 1977 .
[15] Jing Wang,et al. Convergence of batch gradient learning algorithm with smoothing L1/2 regularization for Sigma-Pi-Sigma neural networks , 2015, Neurocomputing.
[16] Nan Nan,et al. Strong Convergence Analysis of Batch Gradient-Based Learning Algorithm for Training Pi-Sigma Network Based on TSK Fuzzy Models , 2015, Neural Processing Letters.