• Publications
  • Influence
New results on recurrent network training: unifying the algorithms and accelerating convergence
How to efficiently train recurrent networks remains a challenging and active research topic. Expand
  • 331
  • 30
  • PDF
A method for dynamic simulation of air-gap eccentricity in induction machines
In this paper, a method is proposed which enables the simulation of the air-gap eccentricity in induction machines. The method is based on the coupled magnetic circuit approach. The model is derivedExpand
  • 204
  • 9
Multi-step-ahead prediction using dynamic recurrent neural networks
In numerous problems, such as in process control utilizing predictive control algorithms, it is required that a variable of interest be predicted multiple time-steps ahead into the future without having measurements in the horizon of interest. Expand
  • 82
  • 8
  • PDF
Induction motor fault diagnosis based on neuropredictors and wavelet signal processing
Early detection and diagnosis of incipient faults is desirable for online condition assessment, product quality assurance and improved operational efficiency of induction motors running off powerExpand
  • 181
  • 7
  • PDF
Prediction of MPEG-coded video source traffic using recurrent neural networks
This paper provides an approach for developing MPEG-coded real-time video traffic predictors for use in single-step (SS) and multistep (MS) prediction horizons. Expand
  • 70
  • 4
  • PDF
Study of three phase induction motors with incipient rotor cage faults under different supply conditions
The majority of rotor related faults in three-phase induction motors are due to broken bars and end rings. These faults occur primarily due to the thermal, magnetic, mechanical, environmentalExpand
  • 51
  • 3
Nonlinear control of U-tube steam generators via H∞ control
Abstract The objective of this paper is to design, analyze and evaluate a controller for the water level of U-tube steam generators. The control objective is to closely regulate the water levelExpand
  • 56
  • 2
Application of the recurrent multilayer perceptron in modeling complex process dynamics
A nonlinear dynamic model is developed for a process system, namely a heat exchanger, using the recurrent multilayer perceptron network as the underlying model structure. Expand
  • 185
  • 2
An accelerated learning algorithm for multilayer perceptron networks
An accelerated learning algorithm (ABP-adaptive back propagation) is proposed for the supervised training of multilayer perceptron networks. Expand
  • 118
  • 2