Gestural control of sonic swarms: Composing with grouped sound objects

This paper outlines an alternative controller designed to diffuse and manipulate a swarm of sounds in 3- dimensional space and discusses the compositional issues that emerge from its use. The system uses an algorithm from a nature-derived model describing the spatial behavior of a swarm. The movement of the swarm is mapped in the 3- dimensional space and a series of sound transformation functions for the sonic agents are implemented. The notion of causal relationships is explored regarding the spatial movement of the swarm and sound transformation of the agents by employing the physical controller as a performance, compositional and diffusion tool

Extremal optimization for sensor report pre-processing

We describe the recently introduced extremal optimization algorithm and apply it to target detection and association problems arising in pre-processing for multi-target tracking. Here we consider the problem of pre-processing for multiple target tracking when the number of sensor reports received is very large and arrives in large bursts. In this case, it is sometimes necessary to pre-process reports before sending them to tracking modules in the fusion system. The pre-processing step associates reports to known tracks (or initializes new tracks for reports on objects that have not been seen before). It could also be used as a pre-process step before clustering, e.g., in order to test how many clusters to use. The pre-processing is done by solving an approximate version of the original problem. In this approximation, not all pair-wise conflicts are calculated. The approximation relies on knowing how many such pair-wise conflicts that are necessary to compute. To determine this, results on phase-transitions occurring when coloring (or clustering) large random instances of a particular graph ensemble are used.Comment: 10 page