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Showing result 1 - 5 of 78 swedish dissertations matching the above criteria.

  2. 1. Regularization for Sparseness and Smoothness : Applications in System Identification and Signal Processing

    Author : Henrik Ohlsson; Lennart Ljung; Jacob Roll; Bo Wahlberg; Linköpings universitet; []
    Keywords : Regularization; sparsity; smothness; lasso; l1; fMRI; bio-feedback; TECHNOLOGY; TEKNIKVETENSKAP;

    Abstract : In system identification, the Akaike Information Criterion (AIC) is a well known method to balance the model fit against model complexity. Regularization here acts as a price on model complexity. READ MORE

  4. 2. Comparative network analysis of human cancer: sparse graphical models with modular constraints and sample size correction

    Author : José Sánchez; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Inverse covariance matrix; precision matrix; graphical models; high-dimension; low-sample; networks; sparsity; fused lasso; elastic net; cancer.; fused lasso;

    Abstract : In the study of transcriptional data for different groups (e.g. cancer types) it's reasonable to assume that some dependencies between genes on a transcriptional or genetic variants level are common across groups. Also, that this property is preserved locally, thus defining a modular structure in the model networks. READ MORE

  5. 3. Network models with applications to genomic data: generalization, validation and uncertainty assessment

    Author : José Sánchez; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Inverse covariance matrix; precision matrix; graphical models; high-dimension; low-sample; networks; sparsity; fused lasso; elastic net; cancer; TCGA pan cancer analysis; online resource; discriminant analysis; classification; networks;

    Abstract : The aim of this thesis is to provide a framework for the estimation and analysis of transcription networks in human cancer. The methods we develop are applied to data collected by The Cancer Genome Atlas (TCGA) and supporting simulations are based on derived models in order to reflect real data structure. READ MORE

  6. 4. Accurate techniques for 2D electromagnetic scattering

    Author : Imad Akeab; Sven-Erik Sandström; Alexander Nosich; Linnéuniversitetet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Integral equations; method of moments; sparsity; scaling; shadow boundary; B-S;

    Abstract : This thesis consists of three parts. The first part is an introduction and referencessome recent work on 2D electromagnetic scattering problems at high frequencies. It alsopresents the basic integral equation types for impenetrable objects. A brief discussionof the standard elements of the method of moments is followed by summaries of thepapers. READ MORE

  7. 5. Resampling in network modeling of high-dimensional genomic data

    Author : Jonatan Kallus; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; high-dimensional data; sparsity; model selection; bootstrap; genomics; graphical modeling;

    Abstract : Network modeling is an effective approach for the interpretation of high-dimensional data sets for which a sparse dependence structure can be assumed. Genomic data is a challenging and important example. In genomics, network modeling aids the discovery of biological mechanistic relationships and therapeutic targets. READ MORE