This paper proposes a method to solve problem that comes with imbalanced training sets which is often seen in the practical applications. We modied Self Growing Neural Network Co...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
: This paper presents a new path-tracking scheme for a car-like mobile robot based on neural predictive control. A multi-layer back-propagation neural network is employed to model ...
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results fro...
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...