Sökning: "signal selection"

Visar resultat 1 - 5 av 202 avhandlingar innehållade orden signal selection.

1. 1. Model Selection

   Författare :Yngve Selén; Peter Stoica; Uppsala universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

   Sammanfattning : Before using a parametric model one has to be sure that it offers a reasonable description of the system to be modeled. If a bad model structure is employed, the obtained model will also be bad, no matter how good is the parameter estimation method. There exist many possible ways of validating candidate models. LÄS MER

3. 2. Model Selection and Sparse Modeling

   Författare :Yngve Selén; Peter Stoica; Jean-Jacques Fuchs; Uppsala universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; model selection; model order selection; model averaging; nested models; sparse models; Bayesian inference; MMSE estimation; MAP estimation; ML estimation; AIC; BIC; GIC; RAKE receivers; pulse compression; radar; linear models; linear regression models; Signal processing; Signalbehandling;

   Sammanfattning : Parametric signal models are used in a multitude of signal processing applications. This thesis deals with signals for which there are many candidate models, and it is not a priori known which model is the most appropriate one. LÄS MER

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

   Författare :Ted Kronvall; Statistical Signal Processing Group; []
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

5. 4. Robust inference of gene regulatory networks : System properties, variable selection, subnetworks, and design of experiments

   Författare :Torbjörn E. M. Nordling; Elling W Jacobsen; Rolf Findeisen; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; network inference; reverse engineering; variable selection; model selection; feature selection; subset selection; system identification; system theory; network theory; subnetworks; design of experiments; perturbation experiments; gene regulatory networks; biological networks;

   Sammanfattning : In this thesis, inference of biological networks from in vivo data generated by perturbation experiments is considered, i.e. deduction of causal interactions that exist among the observed variables. Knowledge of such regulatory influences is essential in biology. LÄS MER

7. 5. Parameter Estimation and Waveform Fitting for Narrowband Signals

   Författare :Tomas Andersson; Peter Händel; István Kollár; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Signal Processing; Signalbehandling; Signal processing; Signalbehandling;

   Sammanfattning : Frequency estimation has been studied for a large number of years. One reason for this is that the problem is easy to understand, but difficult to solve. Another reason, for sure, is the large number of applications that involve frequency estimation, e. LÄS MER