Search for dissertations about: "maximum covariance analysis"

Showing result 1 - 5 of 16 swedish dissertations containing the words maximum covariance analysis.

  2. 1. Spectral Analysis of Nonuniformly Sampled Data and Applications

    Author : Prabhu Babu; Peter Stoica; Fredrik Gustafsson; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Spectral analysis; array processing; nonuniform sampling; sparse parameter estimation; direction of arrival DOA estimation; covariance fitting; sinusoidal parameter estimation; maximum-likelihood; non-parametric approach; exoplanet detection; radial velocity technique; Sudoku; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

    Abstract : Signal acquisition, signal reconstruction and analysis of spectrum of the signal are the three most important steps in signal processing and they are found in almost all of the modern day hardware. In most of the signal processing hardware, the signal of interest is sampled at uniform intervals satisfying some conditions like Nyquist rate. READ MORE

  4. 2. Analysis of Some Methods for Identifying Dynamic Errors-in-variables Systems

    Author : Mei Hong; Torsten Söderström; Magnus Jansson; Uppsala universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; system identification; errors-in-variables; least squares; instrumental variable; maximum likelihood; bias compensated least squares; bias eliminating least squares; Frisch scheme; higher-order statistics; accuracy analysis; periodic data; Signal processing; Signalbehandling;

    Abstract : A system where errors or noises are present on both the inputs and the outputs is called an errors-in-variables (EIV) system. EIV systems appear in industrial and agricultural processes, medical sciences, economical systems, biotechnology, as well as in many other areas. READ MORE

  5. 3. Essays on Estimation Methods for Factor Models and Structural Equation Models

    Author : Shaobo Jin; Fan Yang-Wallentin; Rolf Larsson; Li Cai; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; shrinkage; factor rotation; penalized maximum likelihood; pseudo-maximum likelihood; multi-group analysis; ordinal data; robustness; Statistics; Statistik;

    Abstract : This thesis which consists of four papers is concerned with estimation methods in factor analysis and structural equation models. New estimation methods are proposed and investigated.In paper I an approximation of the penalized maximum likelihood (ML) is introduced to fit an exploratory factor analysis model. READ MORE

  6. 4. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing

    Author : Ted Kronvall; Statistical Signal Processing Group; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; sparse regression; group-sparsity; statistical modeling; regularization; hyperparameter-selection; spectral analysis; audio signal processing; classification; localization; multi-pitch estimation; chroma; convex optimization; ADMM; cyclic coordinate descent; proximal gradient;

    Abstract : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. READ MORE

  7. 5. On performance analysis of subspace methods in system identification and sensor array processing

    Author : Magnus Jansson; Bo Wahlberg; Mats Molander; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; subspace methods; system identification; state-space models; linear regression; sensor array processing; performance analysis; EM algorithm; minimum redundancy array;

    Abstract : This thesis addresses the issue of performance analysis of subspace-based parameter estimation methods in two different applications, namely system identification and sensor array processing.  The objective is to study the quality of the estimated models as the amount of data increases, and to suggest improvements and give user guidelines. READ MORE