Search for dissertations about: "signal-to-noise ratio"

Showing result 6 - 10 of 224 swedish dissertations containing the words signal-to-noise ratio.

2. 6. AVHRR NDVI for monitoring and mapping of vegetation and drought in East African environments

   Author : Lars Eklundh; Institutionen för naturgeografi och ekosystemvetenskap; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Geologi; fysisk geografi; physical geography; Geology; phenology; seasonality; Fourier series; geostatistics; signal-to-noise ratio;

   Abstract : In this thesis, an assessment is made of the performance of the Normalized Difference Vegetation Index (NDVI) derived from coarse resolution data from the NOAA AVHRR sensor, with particular reference to mapping and monitoring of drought and vegetation in East African vegetation and climatic conditions. Methods for analysing time series of satellite data are investigated. READ MORE

4. 7. Ommatidial adaptations for vision in nocturnal insects

   Author : Rikard Frederiksen; Biologiska institutionen; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Gain of transduction; Information rate; Signal-to-noise ratio; Apposition eye; Optical sensitivity; Nocturnal insects; Superposition eye; Vision;

   Abstract : Nocturnal vision is a demanding task for insects with small eyes. As it gets dimmer the noise imposed by the stochastic nature of photon arrival makes vision unreliable. Despite this, there are quite a number of animal species that are active at night and apparently see well. READ MORE

5. 8. Signal identification for visual electrophysiological recordings. A comparison of signal analysis techniques and their application to clinical electrophysiology of vision

   Author : Thomas Wright; Göteborgs universitet; []
   Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Visual Electrophysiology; Signal detection; Signal-to-Noise Ratio; multivariate analysis; spatial-temporal partial least-squares;

   Abstract : Aims: The aim of this thesis was to investigate the use of objective methods for the analysis of visual electrophysiological recordings. Specifically can signal identification algorithms identify electrophysiological signals and can they be applied to improve clinical testing and analysis? Methods: Automated signal identification algorithms were applied to multifocal electroretinogram (mfERG) and visual evoked potential (VEP) recordings. READ MORE

6. 9. Computerised Microtomography : Non-invasive imaging and analysis of biological samples, with special reference to monitoring development of osteoporosis in small animals

   Author : Mats Stenström; Gudrun Alm Carlsson; Carl Carlsson; Jim Elliot; Linköpings universitet; []
   Keywords : Computed microtomography; CμT; signal-to-noise ratio SNR ; non-invasive monitoring; morphological changes; Gastrectomized Sprague-Dawley; osteoporosis; MEDICINE; MEDICIN;

   Abstract : The use of Computerised microtomography (CμT) in biomedical research is well established, with most applications developed at synchrotron facilities. The possibility to non-invasively monitor morphological changes in biological samples, makes it an attractive technique in biomedicine. READ MORE

7. 10. Search for Type 2 Diabetes Susceptibility Genes Using Multiple Approaches

   Author : Cecilia Lindgren; Malmö Institutionen för kliniska vetenskaper; []
   Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; single nucleotide polymorphism SNP ; transmission-disequilibrium test TDT ; genetic variation; single strand conformational polymorphism SSCP ; gene expression; insulin; glucose; genome-wide scan; linkage; genetic association; Type 2 diabetes; early onset diabetes EOD ; sekretion; diabetologi; Endokrinologi; diabetology; Endocrinology; secreting systems; signal-to-noise ratio SNR ;

   Abstract : Type 2 diabetes mellitus is a multifactorial disorder characterized by chronic hyperglycemia resulting from pancreatic dysfunction and insulin resistance. It is a common disorder with a complex pattern of inheritance, likely to reflect the influence of multiple genetic and environmental factors on the diabetes risk. READ MORE