In this paper, we review our work on a time series forecasting methodology based on the combination of unsupervised clustering and artificial neural networks. To address noise and...
Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitr...
A robust adaptive fuzzy neural network (RAFNN) backstepping control system is proposed to control the position of an - -2motion control stage using linear ultrasonic motors (LUSMs)...
A method for the development of empirical predictive models for complex processes is presented. The models are capable of performing accurate multi-step-ahead (MS) predictions, wh...
We design new feed-forward multi-layered neural networks which perform di erent elementary arithmetic operations, such as bit shifting, addition of N p-bit numbers, and multiplica...
Neural network language models (NNLM) have become an increasingly popular choice for large vocabulary continuous speech recognition (LVCSR) tasks, due to their inherent generalisa...
Junho Park, Xunying Liu, Mark J. F. Gales, Philip ...