We give an exposition to an ongoing research effort in cooperation with aerospace industries in Sweden. We report on an application of formal verification techniques on a landing gear system. This system consists of actuating hydromechanic and electromechanic hardware, and of controlling software components. We emphasize the need for modelling techniques and languages covering the whole spectrum from informal engineering documents, to hybrid mathematical models. In this modelling process we give as much weight to the physical environment as to the controlling software. We show the application of two verification methods for proving safety and timeliness properties of the closed loop system; first, using the proof system of extended duration calculus, and second by symbolic model checking.

The concept of tree classifiers is combined with the popular neural net structure. Instead of having one large neural net to capture all the regions in the feature space, the authors suggest the compromise of using small single-output nets at each tree node. This hybrid classifier is referred to as a neural tree. The performance of this classifier is evaluated on real data from a problem in speech recognition. When verified on this particular problem, it turns out that the classifier concept drastically reduces the computational complexity compared with conventional multilevel neural nets. It is also noted that these data make it possible to grow trees online from a continuous data stream.>