A Generalized Growing and Pruning RBF (GGAP-RBF) Neural Network for Function Approximation

An efficient sequential learning algorit

An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks

✍ Guang-Bin Huang; Saratchandran, P.; Sundararajan, N. 📂 Article 📅 2004 🏛 IEEE 🌐 English ⚖ 408 KB

Radial Basis Function (RBF) Neural Netwo

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems || RBF Neural Network Design and Simulation

✍ Liu, Jinkun 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 607 KB

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design metho

RBF neural network based on q-Gaussian f

RBF neural network based on q-Gaussian function in function approximation

✍ Zhao, Wei ;San, Ye 📂 Article 📅 2011 🏛 Higher Education Press and Springer 🌐 English ⚖ 159 KB

Radial Basis Function (RBF) Neural Netwo

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems || Adaptive RBF Control Based on Global Approximation

✍ Liu, Jinkun 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 924 KB

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design metho

Radial Basis Function (RBF) Neural Netwo

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems || Adaptive Robust RBF Control Based on Local Approximation

✍ Liu, Jinkun 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 750 KB

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design metho

Approximation of continuous and disconti

Approximation of continuous and discontinuous mappings by a growing neural RBF-based algorithm

✍ A. Esposito; M. Marinaro; D. Oricchio; S. Scarpetta 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 755 KB