Over the last decade or so, artificial neural networks (ANNs) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. However, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. For this reason, this study aims at de...

The paper extends a previously proposed method for improving the path accuracy of robots. Especially during high speed movements nonlinear couplings between the joints deteriorate and degrade the robot's accuracy. Such couplings cannot be compensated by linear feedforward control. They require additionally a general function approximator as e. g. a multilayer perceptron. The learning system tra...

An auto adaptive neuro-fuzzy segmentation and edge detection architecture is presented. This system consists of a multilayer perceptron (MLP)-like network that performs image segmentation by adaptive thresholding of the input image using labels automatically pre-selected by kernel based fuzzy clustering technique. The proposed architecture is feed forward, but unlike the conventional MLP the le...

The objective of this work was to develop a classification system in order to confirm the authenticity of Galician potatoes with a Certified Brand of Origin and Quality (CBOQ) and to differentiate them from other potatoes that did not have this quality brand. Elemental analysis (K, Na, Rb, Li, Zn, Fe, Mn, Cu, Mg and Ca) of potatoes was performed by atomic spectroscopy in 307 samples belonging t...

Iterative learning control is a feedforward control technique applied to systems or processes that operate in a repetitive fashion over a fixed interval of time to improve tracking/regulation performance in response to reference inputs/disturbance inputs that are repeatable in each cycle. In this paper, learning control is applied to coil-to-coil gauge and tension control during the thread-up p...

This thesis proposal discusses control of dynamic systems and its relation to time. Although much research has been done concerning control of dynamic systems and decision making, little research exists about the relationship between time and control. Control is defined as the ability to keep a target system/ process in a desired state. In this study, properties of time such as fast, slow, over...

The present report summarizes the work conducted during the internship on Feedforward Control of the Magnetic Levitation Setup. Different feedforward strategies, specifically tailored for this setup, are developed and reviewed. These feedforward methods explicitly take the intrinsic position-dependent behavior of the magnetic levitation setup into account. Additionally, closed-loop stability of...

The system operates in two modes : bootstrap and feed forward mode. In bootstrap mode a portion of the image is segmented, the texture boundary is located, and all of the parameters necessary for configuring the system are found. These include the resolution of the segmentation, identification of the most effective features for distinguishing between the two textures, and an estimate of the tex...

Gatys et al. recently demonstrated that deep networks can generate beautiful textures and stylized images from a single texture example. However, their methods require a slow and memoryconsuming optimization process. We propose here an alternative approach that moves the computational burden to a learning stage. Given a single example of a texture, our approach trains compact feed-forward convo...