Sökning: "Multiple Input Multiple Output"

Visar resultat 1 - 5 av 126 uppsatser innehållade orden Multiple Input Multiple Output.

  1. 1. Using unsupervised classification with multiple LDA derived models for text generation based on noisy and sensitive data

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

    Författare :Lucas Ljungberg; [2019]
    Nyckelord :;

    Sammanfattning : Creating models to generate contextual responses to input queries is a difficult problem. It is even more difficult when available data contains noise and sensitive data. Finding models or methods to handle such issues is important in order to use data for productive means. LÄS MER

  2. 2. Modelling and Control of Heat Distribution in a Powder Bed Fusion 3D Printer

    Master-uppsats, Linköpings universitet/Reglerteknik; Linköpings universitet/Reglerteknik

    Författare :Jonathan Hanses; Morten Eriksson; [2019]
    Nyckelord :Control; Modelling; 3D printer; PBF; Heat Distribution;

    Sammanfattning : This thesis report describes how to improve the control of the temperature in a Powder Bed Fusion 3D printer. This is accomplished by first creating a model ofthe thermal system. To create a good model, both black-box and grey-box models of the system are estimated and compared. LÄS MER

  3. 3. Revision of an artificial neural network enabling industrial sorting

    Master-uppsats, Uppsala universitet/Institutionen för teknikvetenskaper

    Författare :Henrik Malmgren; [2019]
    Nyckelord :artificial neural networks; machine learning; deep learning; connectionism; pattern recognition; machine learning; automation; image analysis; information technology; applied mathematics; mathematical optimization; information theory; mathematical statistics; mathematical models; stochastic models; probabilities; chance; approximations; algorithms; computer programs; computer software; signal processing; high performance computing; numerical methods; high technology industries; sustainable development; artificiella neurala nätverk; maskininlärning; djup maskininlärning; konnektionism; mönsterigenkänning; automatisering; bildanalys; informationsteknik; tillämpad matematik; optimering; informationsteori; statistisk inferens; matematiska modeller; stokastiska modeller; sannolikhetskalkyl; slumpen; approximationer; algoritmer; datorprogram; programvara; signalbehandling; högpresterande beräkningar; numeriska metoder; teknikutveckling; maskinindustri; högteknologisk industri; maskinhandel; skrothandel; bärkraftig utveckling;

    Sammanfattning : Convolutional artificial neural networks can be applied for image-based object classification to inform automated actions, such as handling of objects on a production line. The present thesis describes theoretical background for creating a classifier and explores the effects of introducing a set of relatively recent techniques to an existing ensemble of classifiers in use for an industrial sorting system. LÄS MER

  4. 4. The management of dynamic service innovation capabilities in different types of service innovation

    Magister-uppsats, Lunds universitet/Företagsekonomiska institutionen

    Författare :Bilal El Ghalbzouri; Michiel Dröge; [2019]
    Nyckelord :Service innovation management; service innovation process; archetypes of service innovation; dynamic service innovation capabilities; service resources; knowledge integration; service delivery design; service offering; Business and Economics;

    Sammanfattning : Abstract Research questions: Which dynamic service innovation capabilities are used in different types of service innovation? How are they used in the different types? And why does their application vary? Methodology: The study has been conducted through investigating multiple cases within a single case company and followed a qualitative research strategy to identify (the application of) dynamic service innovation capabilities in the archetypes of service innovation. The data was collected through a combination of unstructured and semi-structured interviews and analysed based on the approach presented by Eisenhardt (1989). LÄS MER

  5. 5. Designing a deep-learning network for traffic density and volume prediction

    Kandidat-uppsats, Lunds universitet/Matematik LTH

    Författare :Simon Sjögren; [2019]
    Nyckelord :Mathematics and Statistics;

    Sammanfattning : It is relatively easy to know the day to day traffic flow on a highway without taking into account on which lane the cars are driving on. It is more difficult to understand how traffic over time evolves while looking at the lanes, or more specifically, by looking at traffic volume on the specific lanes on a highway, can we have a good guess for where the vehicles should be on a different lane of the same highway in the future? And could it also be possible to predict future congestion in one juncture by looking at incoming traffic from the past at another or multiple junctions somewhere else? This project serves as a precursor for possible future projects by looking at how traffic volume on a given road with 5 lanes evolves over time. LÄS MER