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Visar resultat 1 - 5 av 20 avhandlingar som matchar ovanstående sökkriterier.
1. Exploiting Prior Information in Parametric Estimation Problems for Multi-Channel Signal Processing Applications
Sammanfattning : This thesis addresses a number of problems all related to parameter estimation in sensor array processing. The unifying theme is that some of these parameters are known before the measurements are acquired. LÄS MER
2. Ultrasonic measurement principles : modeling, identification, and parameter estimation
Sammanfattning : This thesis presents contributions within the fields of ultrasonic modeling and measurement technology, with focus on solutions to difficult modeling and measurement problems. The work is divided into two categories: 1) processing of measurements obtained under non-ideal conditions, such as unsynchronized, distorted, and superimposed signals; 2) estimating acoustic models and parameters from materials, fluids, fluid mixtures, and thin-layered structures. LÄS MER
3. Aspects of analysis of small-sample right censored data using generalized Wilcoxon rank tests
Sammanfattning : The estimated bias and variance of commonly applied and jackknife variance estimators and observed significance level and power of standardised generalized Wilcoxon linear rank sum test statistics and tests, respectively, of Gehan and Prentice are compared in a Monte Carlo simulation study. The variance estimators are the permutational-, the conditional permutational- and the jackknife variance estimators of the test statistic of Gehan, and the asymptotic- and the jackknife variance estimators of the test statistic of Prentice. LÄS MER
4. Inverse problems in signal processing : Functional optimization, parameter estimation and machine learning
Sammanfattning : Inverse problems arise in any scientific endeavor. Indeed, it is seldom the case that our senses or basic instruments, i.e., the data, provide the answer we seek. LÄS MER
5. Sparse Modeling of Grouped Line Spectra
Sammanfattning : This licentiate thesis focuses on clustered parametric models for estimation of line spectra, when the spectral content of a signal source is assumed to exhibit some form of grouping. Different from previous parametric approaches, which generally require explicit knowledge of the model orders, this thesis exploits sparse modeling, where the orders are implicitly chosen. LÄS MER