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A Framework for Linear Control over Channels with Signal-to-Noise Ratio Constraints

We present a framework for the solution of control and estimation problems under a signal-to-noise (SNR) ratio constraint. The framework can be used to design optimal linear controllers, based on output feedback, with two degrees of freedom: One part of the controller is placed before the communication channel and represents sensing and encoding operations. The other part represents decoding and i

Optimizing Parametric Total Variation Models

One of the key factors for the success of recent energy minimization methods is that they seek to compute global solutions. Even for non-convex energy functionals, optimization methods such as graph cuts have proven to produce high-quality solutions by iterative minimization based on large neighborhoods, making them less vulnerable to local minima. Our approach takes this a step further by enlargi

Multi-agent gradient climbing via extremum seeking control

A unified framework based on discrete-time gradient-based extremum seeking control is proposed to localise an extremum of an unknown scalar field distribution using a group of equipped with sensors. The controller utilises estimates of gradients of the field from local dithering sensor measurements collected by the mobile agents. It is assumed that distributed coordination which ensures uniform as

Designing learning environments for heterogeneous groups in Second Life

The project that we will discuss in this paper aims to support the areas of teaching and learning in a multidisciplinary collaboration between the Centre for Languages and Literature (SOL), Faculty of Engineering (LTH) and Centre for Educational Development (CED), all Lund University, Sweden, by using the virtual world Second Life (SL) as a platform for collaborative learning activities. Students