Sökning: "gaussian mixture regression"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden gaussian mixture regression.

  1. 1. Regression with Bayesian Confidence Propagating Neural Networks

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

    Författare :Raghav Rajendran Bongole; [2023]
    Nyckelord :Machine Learning; Neural Networks; Brain-like computing; Bayesian Confidence Propagating Neural Networks; Maskininlärning; neurala nätverk; hjärnliknande datorer; Bayesian Förtroendespridande neurala nätverk;

    Sammanfattning : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. LÄS MER

  3. 2. Predicting Quality of Experience from Performance Indicators : Modelling aggregated user survey responses based on telecommunications networks performance indicators

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

    Författare :Christian Vestergaard; [2022]
    Nyckelord :Quality of Experience; Telecommunication; Regression; Long Short Term Memmory; Clustering; K-means; Gaussian Mixture Models; Användarupplevelse; Telekommunikation; Regression; Long Short Term Memmory; Klusteranalys; K-means; Gaussian Mixture Models;

    Sammanfattning : As user experience can be a competitive edge, it lies in the interest of businesses to be aware of how users perceive the services they provide. For telecommunications operators, how network performance influences user experience is critical. To attain this knowledge, one can survey users. LÄS MER

  4. 3. Statistical Modelling of Plug-In Hybrid Fuel Consumption : A study using data science methods on test fleet driving data

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Theodor Matteusson; Niclas Persson; [2020]
    Nyckelord :Machine learning; Data science; Plug-in hybrid electric vehicle; Charge depletion; Charge sustaining; Fuel consumption; Maskininlärning; Data science; Ladd-hybrider; Charge depletion; Charge sustaining; Bränsleförbrukning;

    Sammanfattning : The automotive industry is undertaking major technological steps in an effort to reduce emissions and fight climate change. To reduce the reliability on fossil fuels a lot of research is invested into electric motors (EM) and their applications. LÄS MER

  5. 4. Automatic Speech Quality Assessment in Unified Communication : A Case Study

    Master-uppsats, Linköpings universitet/Programvara och system

    Författare :Kevin Larsson Alm; [2019]
    Nyckelord :speech; voice; communication; qoe; quality of experience; unified communication; uc; speech quality assessment; speech quality; voice calls; gaussian mixture model; gmm; gaussian mixture regression; gmr; mel frequency cepstrum coefficients; mfcc; human feature cepstrum coefficients; hfcc; gammatone frequency cepstral coefficients; gfcc;

    Sammanfattning : Speech as a medium for communication has always been important in its ability to convey our ideas, personality and emotions. It is therefore not strange that Quality of Experience (QoE) becomes central to any business relying on voice communication. LÄS MER

  7. 5. Gaussian Process Regression-based GPS Variance Estimation and Trajectory Forecasting

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap; Linköpings universitet/Tekniska fakulteten

    Författare :Linus Kortesalmi; [2018]
    Nyckelord :Machine Learning; GPR; Gaussian Process; GP; Gaussian Process Regression; Variance Estimation; Trajectory; Trajectory Forecasting; Regression; Gaussiska Processer; Variansestimering; trajektoria; Statistik; Maskininlärning;

    Sammanfattning : Spatio-temporal data is a commonly used source of information. Using machine learning to analyse this kind of data can lead to many interesting and useful insights. In this thesis project, a novel public transportation spatio-temporal dataset is explored and analysed. LÄS MER