Sökning: "analys modell nätverk"

Visar resultat 1 - 5 av 70 uppsatser innehållade orden analys modell nätverk.

  1. 1. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

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

    Författare :Eddie Nevander Hellström; Johan Slettengren; [2023]
    Nyckelord :;

    Sammanfattning : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. LÄS MER

  3. 2. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

  4. 3. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Nazar Maksymchuk Netterström; [2023]
    Nyckelord :Recurrent Neural Network; Long-Short-Term-Memory; Topological Data Analysis; Session based data; Anomaly detection; Time-series analysis; Imbalanced data; Master thesis; Neurala nätverk; Topologisk data analys; Detektion av avvikelse; Sessionsbaserad data; Tidserieanalys; Inbalancerad data; Masteruppsats;

    Sammanfattning : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. LÄS MER

  5. 4. 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

  7. 5. Comparison of Operator and Nonoperator Managed 5G Non-Public Networks (NPNs): Implications for Network Architectures and Cost Structures

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

    Författare :Amina Ahmed; [2023]
    Nyckelord :;

    Sammanfattning : In the evolving landscape of communication technologies, 5G Non-Public Network (NPN) enables organizations, enterprises, and industries to have specialized, highperformance connectivity tailored to their needs. It operates independently of Mobile Public Networks (MNOs) and is designed to provide secure, low-latency, and reliable communication in two broad types: standalone or public-integrated. LÄS MER