We investigate the semigroup structure of bosonic Gaussian quantum channels. Particular focus lies on the sets of channels which are divisible, idempotent or Markovian (in the sense of either belonging to one-parameter semigroups or being infinitesimal divisible). We show that the non-compactness of the set of Gaussian channels allows for remarkable differences when comparing the semigroup stru...

We propose a new method for smoothing 2-D (or 3-D) images which preserves edge elements. Pixel data contained within a moving square (or cube), centered at each point under consideration, is tested to determine if it is homogeneous, or if a region boundary is present. If the area is homogeneous, the mean value of the whole area gives the smoothed value for the central point. If a region boundar...

This paper proposes an automatic method for artefact removal and noise elimination from scalp electroencephalogram recordings (EEG). The method is based on blind source separation (BSS) and supervised classification and proposes a combination of classical and news features and classes to improve artefact elimination (ocular, high frequency muscle and ECG artefacts). The role of a supplementary ...

-In this paper we present new approximation expressions for the Cramer-Rao Lower Bound on unbiased estimates of frequency, phase, amplitude and DC offset for uniformly sampled signal embedded in white-Gaussian noise. This derivation is based on well-known assumptions and a novel set of approximations for finite series of trigonometric functions. The estimated Cramer-Rao Lower Bounds are given i...

Interesting signals are often contaminated by heavy-tailed noise that has more outliers than Gaussian noise. Under the introduction of probability model for heavy-tailed noises, a robust wavelet threshold based on the minimax description length principle is derived in the εcontaminated normal family for maximizing the entropy. The performance and their measurement criterion for the robust wavel...

NASA Tech Briefs, November 2010 yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior. This work was done by Baris I. Erkmen and Bruce E. Moision of Caltech for NASA’s Jet Propulsion...

Matching pursuit (MP) is an adaptive signal decomposition technique and can be applied to process Lamb waves, such as denoising, wave parameter estimation, and feature extraction, for health monitoring applications. This paper explored matching pursuit decomposition using Gaussian and chirplet dictionaries to decompose/approximate Lamb waves and extract wave parameters. While Gaussian dictionar...

In an earlier paper the authors described a very fast method which, for the root lattices A,, D,, E,,, their duals and certain other lattices, finds the closest lattice point to an arbitrary point of the underlying space. If the lattices are used as codes for a Gaussian channel, the algorithm provides a fast decoding procedure, or if they are used as vector quantizers the algorithm performs the...

Differential privacy mechanism design has traditionally been tailored for a scalar-valued query function. Although many mechanisms such as the Laplace and Gaussian mechanisms can be extended to a matrix-valued query function by adding i.i.d. noise to each element of the matrix, this method is often suboptimal as it forfeits an opportunity to exploit the structural characteristics typically asso...

NASA Tech Briefs, November 2010 yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior. This work was done by Baris I. Erkmen and Bruce E. Moision of Caltech for NASA’s Jet Propulsion...