Sökning: "Eigenvalue Decomposition"

Visar resultat 1 - 5 av 6 uppsatser innehållade orden Eigenvalue Decomposition.

  1. 1. Analysis, Implementation and Evaluation of Direction Finding Algorithms using GPU Computing

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Regina Andersdotter; [2022]
    Nyckelord :GPU; GPU Computing; Direction Finding; GPU Suitability; CUDA; Multiple Signal Classification; Weighted Subspace Fitting; Correlative Interferometer; runtime; angle resolution; block size;

    Sammanfattning : Direction Finding (DF) algorithms are used by the Swedish Defence Research Agency (FOI) in the context of electronic warfare against radio. Parallelizing these algorithms using a Graphics Processing Unit (GPU) might improve performance, and thereby increase military support capabilities. LÄS MER

  3. 2. Enhancing ESG-Risk Modelling - A study of the dependence structure of sustainable investing

    Master-uppsats, KTH/Matematisk statistik

    Författare :Edvin Berg; Karl Wilhelm Lange; [2020]
    Nyckelord :ESG; Sustainable Investing; Dependency Structure; Correlation; Risk; Random Matrix Theory; Eigenvalue; Eigenvalue Decomposition; Minimum Variance Portfolio; ESG; Hållbar Investering; Beroendestruktur; Korrelation; Stokastisk Matristeori; Egenvärden; Egenvärdes Dekomposition; Minimal Variansportfölj;

    Sammanfattning : The interest in sustainable investing has increased significantly during recent years. Asset managers and institutional investors are urged to invest more sustainable from their stakeholders, reducing their investment universe. LÄS MER

  4. 3. Image Processing using Graph Laplacian Operator

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :David Wobrock; [2019]
    Nyckelord :;

    Sammanfattning : The latest image processing methods are based on global data-dependent filters. These methods involve huge affinity matrices which cannot fit in memory and need to be approximated using spectral decomposition. LÄS MER

  5. 4. On Identification of Hidden Markov Models Using Spectral and Non-Negative Matrix Factorization Methods

    Master-uppsats, KTH/Reglerteknik

    Författare :Robert Mattila; [2015]
    Nyckelord :;

    Sammanfattning : Hidden Markov Models (HMMs) are popular tools for modeling discrete time series. Since the parameters of these models can be hard to derive analytically or directly measure, various algorithms are available for estimating these from observed data. LÄS MER

  7. 5. Implementation of Singly Diagonally Implicit Runge-Kutta Methods with Constant Step Sizes

    Kandidat-uppsats, Lunds universitet/Matematik LTH

    Författare :Josefine Stål; [2015]
    Nyckelord :Implicit Runge-Kutta methods; SDIRK; Implementation; Python; Mathematics and Statistics;

    Sammanfattning : Runge–Kutta methods can be used for solving ordinary differential equations of the form y0 = f(t, y) with initial condition y(t0) = y0 and where f : R x R^m -> R^m. The idea is to find a method that is efficient to implement. But it is also important for the method to be of high order and be stable. LÄS MER