β Scribed by M.C. Campi; P.R. Kumar
No coin nor oath required. For personal study only.
We consider the problem of learning the input-output relation of a dynamical system from noisy data. Our method rests on the use of a smooth simultaneous estimator which generalizes the standard empirical estimator. In a stationary environment, our algorithm is shown to select a model which exhibits the Probably Approximately Correct (PAC) property under very mild conditions. This contribution should be thought of as a ΓΏrst attempt to extend concepts developed in learning theory to the ΓΏeld of system identiΓΏcation where, due to the presence of the system dynamics, the typical i.i.d. assumption on the data made in learning theory is not satisΓΏed.
π SIMILAR VOLUMES
This pilot study represents an initial step to better understand both the potential for and limitations to leaming science when middle school students interact with expert computer simulations; that is, simulations designed by scientists and built by professional programmers. The eight middle school
Like many subjects taught to engineering students, the teaching of system dynamics typically has been based on a traditional didactic approach. However, there appears to be a shift away from the traditional approach to teaching system dynamics toward alternative methods of delivery such as problem-b
## Abstract Numerous studies have demonstrated that annotation is an important part of human reading behavior in both printed and electronic environments. Annotation in the electronic environment requires special support due to limited media affordances. We have witnessed continuous improvement of