Signal processing methods for EEG data classification

Imperial Users onl

Power spectral density estimation for wireless fluctuation enhanced gas sensor nodes

Fluctuation enhanced sensing (FES) is a promising method to improve the selectivity and sensitivity of semiconductor and nanotechnology gas sensors. Most measurement setups include high cost signal conditioning and data acquisition units as well as intensive data processing. However, there are attempts to reduce the cost and energy consumption of the hardware and to find efficient processing methods for low cost wireless solutions. In our paper we propose highly efficient signal processing methods to analyze the power spectral density of fluctuations. These support the development of ultra-low-power intelligent fluctuation enhanced wireless sensor nodes while several further applications are also possible

Classification of data collection methods (= Deliverable 3.1 of the OrganicDataNetwork project - Report on collection methods)

In this report, a number of evaluation and quality criteria for data collection and compilation methods were defined. The results of an online survey on all existing organic market data collection methods in Europe were compiled and assessed. Subsequently the quality of existing data collection and processing approaches was evaluated using the following data quality dimensions: relevance, accuracy, comparability, coherence, accessibility and clarity, and timeliness and punctuality. The quality assessment was carried out exemplary to determine some good examples of data collection and processing. These cases were chosen because they delivered a very holistic and comprehensive presentation of their approaches regarding data collection methods, analyses, quality checks, and publication

Dynamic system identification methods for fMRI data processing

Katedra řídicí technik

The VIRUS-P Exploration of Nearby Galaxies (VENGA): Survey Design, Data Processing, and Spectral Analysis Methods

We present the survey design, data reduction, and spectral fitting pipeline for the VIRUS-P Exploration of Nearby Galaxies (VENGA). VENGA is an integral field spectroscopic survey, which maps the disks of 30 nearby spiral galaxies. Targets span a wide range in Hubble type, star formation activity, morphology, and inclination. The VENGA data-cubes have 5.6'' FWHM spatial resolution, ~5A FWHM spectral resolution, sample the 3600A-6800A range, and cover large areas typically sampling galaxies out to ~0.7 R_25. These data-cubes can be used to produce 2D maps of the star formation rate, dust extinction, electron density, stellar population parameters, the kinematics and chemical abundances of both stars and ionized gas, and other physical quantities derived from the fitting of the stellar spectrum and the measurement of nebular emission lines. To exemplify our methods and the quality of the data, we present the VENGA data-cube on the face-on Sc galaxy NGC 628 (a.k.a. M 74). The VENGA observations of NGC 628 are described, as well as the construction of the data-cube, our spectral fitting method, and the fitting of the stellar and ionized gas velocity fields. We also propose a new method to measure the inclination of nearly face-on systems based on the matching of the stellar and gas rotation curves using asymmetric drift corrections. VENGA will measure relevant physical parameters across different environments within these galaxies, allowing a series of studies on star formation, structure assembly, stellar populations, chemical evolution, galactic feedback, nuclear activity, and the properties of the interstellar medium in massive disk galaxies.Comment: Accepted for publication in AJ, 25 pages, 18 figures, 6 table