This paper discusses the concurrent design of a feedforward time-delay filter and a linear state feed-back controller. The optimization is carried out using a quadratic cost functional which weights both, disturbance rejection and control tracking performance. A minimax optimization scheme is employed to achieve robustness with respect to parameter deviations. Analytical gradients are provided ...

Abstract Logic-based machine learning aims to learn general, interpretable knowledge in a data-efficient manner. However, labelled data must be specified structured logical form. To address this limitation, we propose neural-symbolic framework, called Feed-Forward Neural-Symbolic Learner (FFNSL) , that integrates logic-based system capable of from noisy examples, with neural networks, order uns...

In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...

Introduction Sound vibrations are collected from the external environment by the eardrum and are guided to the basilar membrane in the cochlea. Pressure differences in the two scalae of the cochlea result in a traveling wave on the basilar membrane (figure 1). The tiny displacements are detected by the deflection of thousands of hair cells, situated along this membrane. It is hypothesized that ...