Search for dissertations about: "spectral smoothing"

Showing result 1 - 5 of 8 swedish dissertations containing the words spectral smoothing.

  2. 1. Advanced Spectral Analysis with Applications

    Author : Niclas Sandgren; Peter Stoica; Thomas L. Marzetta; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; frequency-selective spectral analysis; damped sinusoidal model; prior knowledge; multichannel spectroscopy; phantom experimental data; in-vivo in-vitro data analysis; area-selective analysis; cepstrum thresholding; total-variance reduction; two-dimensional spectral estimation; spectral smoothing; irregular sampling; CARMA signals; Signal processing; Signalbehandling;

    Abstract : Spectral analysis has advanced the last decades as a signal processing tool to extract significant information about certain properties of measured data. The practical use of spectral analysis techniques in time-series analysis has been emphasized in the immense amount of previous literature in the field and by a rapidly growing number of applications. READ MORE

  4. 2. Spectral Image Processing with Applications in Biotechnology and Pathology

    Author : Milan Gavrilovic; Carolina Wählby; Ewert Bengtsson; Ingrid Carlbom; Robert Murphy; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; color theory; light microscopy; spectral imaging; image analysis; digital image processing; mathematical modeling; estimation; noise models; spectral decomposition; color decomposition; colocalization; cross-talk; autofluorescence; tissue separation; prostate cancer; biomedical applications; molecular biotechnology; histopathology; Computerized Image Processing; Datoriserad bildbehandling;

    Abstract : Color theory was first formalized in the seventeenth century by Isaac Newton just a couple of decades after the first microscope was built. But it was not until the twentieth century that technological advances led to the integration of color theory, optical spectroscopy and light microscopy through spectral image processing. READ MORE

  5. 3. Spectral analysis and magnetic resonance spectroscopy

    Author : Tomas Sundin; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Nonparametric spectral analysis; magnetic resonance spectroscopy; parameter estimation; maximum likelihood estimation; nonlinear least squares; Signal processing; Signalbehandling; Signal Processing; Signalbehandling;

    Abstract : This dissertation is concerned with nonparametric approaches for spectral analysis (SA) and algorithms for magnetic resonance spectroscopy (MRS) data analysis.A method to obtain the optimal smoothing window for the class of SA methods based on local smoothing of the periodogram is proposed. READ MORE

  6. 4. Multigrid Preconditioners for the Discontinuous Galerkin Spectral Element Method : Construction and Analysis

    Author : Lea Miko Versbach; Numerisk analys; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Discontinuous Galerkin Method; Finite Volume Method; Implicit Schemes; Local Fourier Analysis; Multigrid Method; Preconditioner; Space-Time Discretization; Spectral Element Method;

    Abstract : Discontinuous Galerkin (DG) methods offer a great potential for simulations of turbulent and wall bounded flows with complex geometries since these high-order schemes offer a great potential in handling eddies. Recently, space-time DG methods have become more popular. READ MORE

  7. 5. Enhancement of Salient Image Regions for Visual Object Detection

    Author : Keren Fu; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; geodesic distance; graph spectral decomposition; video processing; visual attention; color contrast and distribution; propagation; salient region; figure-ground segmentation;

    Abstract : Salient object/region detection aims at finding interesting regions in images and videos, since such regions contain important information and easily attract human attention. The detected regions can be further used for more complicated computer vision applications such as object detection and recognition, image compression, content-based image editing, and image retrieval. READ MORE