Abstract not found

Abstract. We classify nonconstant entire local minimizers of the standard Ginzburg-Landau functional for maps in H 1 loc (R3; R 3) satisfying a natural energy bound. Up to translations and rotations, such solutions of the Ginzburg-Landau system are given by an explicit solution equivariant under

In this paper, we analyze technology transfers (TT) and tradable emission rights, which are core issues of the ongoing climate negotiations. Subsidizing TT leads to the adoption of better abatement technologies in developing countries, thereby reducing the international permit price

Abstract not found

~f d1400 Wilson Boulevard nc assi ie

I would like to thank my parents for always believing in me. I would also like to thank my supervisors Richard Lindner and Johannes Buchmann for their useful comments and suggestions on how to improve the queality of the thesis. Not on last place I would like to thank Vadim Lyubashevsky and Luis Carlos Coronado Garcia for their kindness and readiness to answer my questions. Warranty I hereby warrant that the content of this thesis is the direct result of my own work and that any use made in it of published or unpublished material is fully and correctly referenced. I also warrant that the presented work has

Abstract not found

Abstract not found

The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order of the signal complexity. In practice, this enables lower sampling rates that can be more easily achieved by current hardware designs. The primary bottleneck that limits ADC sam-pling rates is quantization, i.e., higher bit-depths impose lower sampling rates. Thus, the decreased sampling rates of CS ADCs accommodate the otherwise limiting quantizer of conventional ADCs. In this thesis, we consider a different approach to CS ADC by shifting towards lower quantizer bit-depths rather than lower sampling rates. We explore the extreme case where each measurement is quantized to just one bit, representing its sign. We develop a new theoretical framework to analyze this extreme case and develop new algorithms for signal reconstruction from such coarsely quantized measurements. The 1-bit CS framework leads us to scenarios where it may be more appropriate to reduce bit-depth instead of sampling rate. We find that there exist two distinct regimes of operation that correspond to high/low signal-to-noise ratio (SNR). In the measurement

messages with an arbitrary set of other source nodes via the relay. By allowing an arbitrary information exchange pattern, the consid-ered channel model is a unified one. It includes several existing channel models as special cases:K-user MIMO Y channel, multi-pair MIMO two-way relay channel, generalized