Sökning: "errors-in-variables models"
Visar resultat 1 - 5 av 7 avhandlingar innehållade orden errors-in-variables models.
1. Identification of dynamic errors-in-variables models
Sammanfattning : The problem of identifying dynamic errors-in-variables models is of fundamental interest in many areas like process control, array signal processing, astronomical data reduction. In recent years, this field has received increased attention of the research community. LÄS MER
2. A covariance structure analysis approach to the errors-in-variables estimation problem
Sammanfattning : It is a well-known fact that standard regression techniques, when applied to errors-in-variables (EIV) models, lead to biased and inconsistent parameter estimation. The work presented in this thesis address the EIV estimation problem using covariance structure analysis (CSA). LÄS MER
3. Continuous-Time Models in Kernel Smoothing
Sammanfattning : This thesis consists of five papers (Papers A-E) treating problems in non-parametric statistics, especially methods of kernel smoothing applied to density estimation for stochastic processes (Papers A-D) and regression analysis (Paper E). A recurrent theme is to, instead of treating highly positively correlated data as ``asymptotically independent'', take advantage of local dependence structures by using continuous-time models. LÄS MER
4. On some continuous-time modeling and estimation problems for control and communication
Sammanfattning : The scope of the thesis is to estimate the parameters of continuous-time models used within control and communication from sampled data with high accuracy and in a computationally efficient way.In the thesis, continuous-time models of systems controlled in a networked environment, errors-in-variables systems, stochastic closed-loop systems, and wireless channels are considered. LÄS MER
5. Indirect System Identification for Unknown Input Problems : With Applications to Ships
Sammanfattning : System identification is used in engineering sciences to build mathematical models from data. A common issue in system identification problems is that the true inputs to the system are not fully known. In this thesis, existing approaches to unknown input problems are classified and some of their properties are analyzed. LÄS MER