Browsing by Author "Jones, D. I."
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- An efficient parallel implementation of a least squares problemPublication . Ruano, Antonio; Fleming, P. J.; Jones, D. I.Least squares solutions are a very important problem, which appear in a broad range of disciplines (for instance, control systems, statistics, signal processing). Our interest in this kind of problems lies in their use of training neural network controllers.
- An efficient parallel implementation of a least squares problemPublication . Ruano, Antonio; Fleming, P. J.; Jones, D. I.Least squares solutions are a very important problem, which appear in a broad range of disciplines (for instance, control systems, statistics, signal processing). Our interest in this kind of problems lies in their use of training neural network controllers.
- Connectionist approach to PID autotuningPublication . Ruano, Antonio; Fleming, P. J.; Jones, D. I.Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulatores comes from their rebust performance in a wide range of operationg conditions, and also from their functional simplicity, which makes them suitable for manual tuning.
- A connectionist approach to PID autotuningPublication . Ruano, Antonio; Fleming, P. J.; Jones, D. I.Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulators comes from their rebust performance in a wide range of operating conditions, and also from their functional simplicity, which makes them suitable for manual tuning.
- A neural network controllerPublication . Ruano, Antonio; Jones, D. I.; Fleming, P. J.Proportional, Integral and Derivative (PID) regulators are standard building blocks for industrial automation. The popularity of these regulators comes from their rebust performance in a wide range of operating conditions, and also from their functional simplicity, which makes them suitable for manual tuning.
- A new formulation of the learning problem for a neural network controllerPublication . Ruano, Antonio; Jones, D. I.; Fleming, P. J.In this paper we consider the learning problem for a class of multilayer perceptrons which is practically relevant in control systems applications. By reformulating this problem, a new criterion is developed, which reduces the number of iterations required for the learning phase.
- Parallel implementation of a learning algorithm for multilayer perceptrons using transputersPublication . Ruano, Antonio; Jones, D. I.; Fleming, P. J.In this paper the parallelization of a new learning algorithm for multilayer perceptrons, specifically targeted for nonlinear function approximation purposes, is discussed. Each major step of the algorithm is parallelized, a special emphasis being put in the most computationally intensive task, a least-squares solution of linear systems of equations.