Sökning: "Long short-term memory nätverk"

Visar resultat 1 - 5 av 90 uppsatser innehållade orden Long short-term memory nätverk.

1. 1. Heart rate estimation from wrist-PPG signals in activity by deep learning methods

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

   Författare :Marie-Ange Stefanos; [2023]
   Nyckelord :Deep Learning; Medical Data; Signal Processing; Heart Rate Estimation; Wrist Photoplethysmography; Djup lärning; Medicinska Data; Signalbehandling; Pulsuppskattning; Handledsfotopletysmograf;

   Sammanfattning : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. LÄS MER

3. 2. Machine Learning for State Estimation in Fighter Aircraft

   Master-uppsats, KTH/Optimeringslära och systemteori

   Författare :Axel Boivie; [2023]
   Nyckelord :State estimation; machine learning; fighter aircraft; neural networks; long short- term memory; LSTM; sensor fusion; air data system; ADS.; Tillståndsestimering; maskininlärning; stridsflygplan; neurala nätverk; sensorfusion; luftdatasystem.;

   Sammanfattning : This thesis presents an estimator to assist or replace a fighter aircraft’s air datasystem (ADS). The estimator is based on machine learning and LSTM neuralnetworks and uses the statistical correlation between states to estimate the angleof attack, angle of sideslip and Mach number using only the internal sensorsof the aircraft. LÄS MER

4. 3. Modelling Proxy Credit Cruves Using Recurrent Neural Networks

   Master-uppsats, KTH/Matematisk statistik

   Författare :Lucas Fageräng; Hugo Thoursie; [2023]
   Nyckelord :Deep Neural Networks; Credit Risk; Financial Modelling; LSTM; Credit Default Swaps; Credit Valuation Adjustment; Djupa Neurala Nätverk; Kreditrisk; Finansiell Modellering; LSTM; Kreditswappar; Kreditvärderingsjustering;

   Sammanfattning : Since the global financial crisis of 2008, regulatory bodies worldwide have implementedincreasingly stringent requirements for measuring and pricing default risk in financialderivatives. Counterparty Credit Risk (CCR) serves as the measure for default risk infinancial derivatives, and Credit Valuation Adjustment (CVA) is the pricing method used toincorporate this default risk into derivatives prices. LÄS MER

5. 4. 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

7. 5. 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