We present an efficient implementation of an approximate balanced truncation model reduction technique for general large-scale RLC systems, described by a statespace model where t...
In this paper we present a wall-sized input system with high accuracy input in the center and lower precision tracking on the remaining parts of the wall. This work complements th...
Inductive inference is concerned with algorithmic learning of recursive functions. In the model of learning in the limit a learner successful for a class of recursive functions mus...
Aggregation of data values plays an important role on distributed computations, in particular over peer-to-peer and sensor networks, as it can provide a summary of some global sys...
—Many large-scale distributed systems can benefit from a service that allows them to select among alternative nodes based on their relative network positions. A variety of appro...