Electrical Excitability: The Basis for Applied Neural Control

A neural basis for the development of in

A neural basis for the development of inhibitory control

✍ Sarah Durston; Kathleen M. Thomas; Yihong Yang; Aziz M. Uluğ; Robert D. Zimmerma 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 411 KB

Applied neural control in the 1990s

✍ Heetderks, W.J.; Hambrecht, F.T. 📂 Article 📅 1988 🏛 IEEE 🌐 English ⚖ 837 KB

Radial Basis Function (RBF) Neural Netwo

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems || Discrete Neural Network Control

✍ Liu, Jinkun 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 497 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

Neural basis for cognitive control enhan

Neural basis for cognitive control enhancement in elderly people

✍ Jeanyung Chey; Hoyoung Kim 📂 Article 📅 2012 🏛 Elsevier Science 🌐 English ⚖ 109 KB

Radial Basis Function (RBF) Neural Netwo

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems || Adaptive RBF Neural Network Control

✍ Liu, Jinkun 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 589 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 || Neural Network Sliding Mode Control

✍ Liu, Jinkun 📂 Article 📅 2012 🏛 Springer Berlin Heidelberg 🌐 German ⚖ 246 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