Detection and Diagnosis of Small Changes in Nonlinear

In this paper, we describe a general approach for detecting small changes, which can be applied to a wide class of nonlinear systems, and which can manage with a reduced order and biased signature of the monitored system. We show how to implement this general approach for solving a real problem, namely the monitoring of the combustion chambers of a gas turbine. Furthermore, we also describe a statistical method for solving the problem of diagnosing the detected changes in the combustion chambers

Asynchronous teams

Abstract: "This paper has three purposes: first, to define a space of organizations for computer-based agents; second, to identify a fuzzy subset (called [delta]3[phi]) of this space that contains organizations that are open, parallel and effective; and third, to illustrate how members (called asynchronous teams) of this subset can be realized. These teams are characterized by autonomous agents that work in parallel on populations of solutions. As such, they have features in common with a number of well known organizations. Blackboards, parallel implementations of genetic algorithms and certain recurrent neural nets are examples. But these examples occur at the very outermost fringes of the [delta]3[phi] subset. Its interior remains unexplored. We begin that exploration here.