NNARX Networks on Didactic Level System Identification

Didactic Networks and Exemplification

After a general overview in a previous paper [10], in which we proposed Didactic Networks (DN) as a new way for developing and exploiting web-learning content, we offer here a deeper study showing how to use them for web-learning design and content generation based on Instructional Theory with the coherence guaranty of the RST [3]. By using a set of expressivity patterns, it is possible to obta...

Didactic System for Object-oriented Modelling

The authors introduce a didactic system for object-oriented modelling (OOM) as a new and flexible learning concept for informatics education and outline a development methodology which is in evaluation. With the aim to improve the quality and individualization of lessons the following components of a didactic system have been identified so far: and-or-graphs for the representation of the knowle...

Neural Networks in System Identification

System identification is an important way of investigating and understanding the world around. Identification is a process of deriving a mathematical model of a predefined part of the world, using observations. There are several different approaches of system identification, and these approaches utilize different forms of knowledge about the system. When only input-output observations are used ...

System Identification Using Neural Networks

Some new results on system identification with dynamic neural networks

Nonlinear system online identification via dynamic neural networks is studied in this paper. The main contribution of the paper is that the passivity approach is applied to access several new stable properties of neuro identification. The conditions for passivity, stability, asymptotic stability, and input-to-state stability are established in certain senses. We conclude that the gradient desce...