With aggressive scaling down of feature sizes in VLSI fabrication, process variation has become a critical issue in designs. We show that two necessary conditions for the "Max...
In this paper we present a method which allows the statistical analysis of nanoelectronic Boolean networks with respect to timing uncertainty and noise. All signals are considered...
Oliver Soffke, Peter Zipf, Tudor Murgan, Manfred G...
This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Ob...
Wavelet-based statistical analysis methods for fMRI are able to detect brain activity without smoothing the data. Typically, the statistical inference is performed in the wavelet ...
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...