Essays about: "Wavelet Transform"

Showing result 1 - 5 of 69 essays containing the words Wavelet Transform.

  1. 1. Data Assimilation for Systems with Multiple Timescales

    University essay from KTH/Skolan för teknikvetenskap (SCI)

    Author : Dan Vicente Ihanus; [2023]
    Keywords : Mathematics; Partial Differential Equations; Numerical analysis; Data assimilation; Numerical weather prediction; Ensemble Kalman Filter;

    Abstract : This text provides an overview of problems in the field of data assimilation. We explore the possibility of recreating unknown data by continuously inserting known data into certain dynamical systems, under certain regularity assumptions. READ MORE

  3. 2. Unsupervised Detection of Interictal Epileptiform Discharges in Routine Scalp EEG : Machine Learning Assisted Epilepsy Diagnosis

    University essay from Uppsala universitet/Avdelningen Vi3

    Author : Shuai Shao; [2023]
    Keywords : EEG; electroencephalography; IED; interictal epileptiform discharges; spike detection; epilepsy; unsupervised; Fourier transform; STFT; short-time Fourier transform; CWT; continuous wavelet transform; DWT; discrete wavelet transform; ML; machine learning; ANN; artificial neural network; CNN; convolutional neural network; autoencoder; HMM; hidden Markov model; ECS; Euclidean distance of cumulative spectrum;

    Abstract : Epilepsy affects more than 50 million people and is one of the most prevalent neurological disorders and has a high impact on the quality of life of those suffering from it. However, 70% of epilepsy patients can live seizure free with proper diagnosis and treatment. Patients are evaluated using scalp EEG recordings which is cheap and non-invasive. READ MORE

  4. 3. Vibroacoustic Analysis of an OLTC Diverter Switch for Condition Monitoring : Time frequency analysis with Fourier and wavelet transform in combination with multivariate logistic regression for condition monitoring of OLTC diverter switch

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Simon Persson; [2023]
    Keywords : Wavelet transform; CWT; logistic regression; machine learning; ML; vibroacoustic analysis; time frequency analysis; tap changer; diverter switch; power transformer; classification; prediction; condition; vibrations; state prediction; Hitachi Energy;

    Abstract : Vibrations are everywhere around us all the time and we often recognise them as sounds that we can hear and analyse with our brain. In this thesis, data that has been gathered from a diverter switch (DS) in a controlled environment, is analysed. READ MORE

  5. 4. Dealing With Speckle Noise in Deep Neural Network Segmentation of Medical Ultrasound Images

    University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Author : Olmo Daniel; [2022]
    Keywords : Deep Learning; Ultrasound; Speckle Filtering; Medical Image Segmentation; U-Net; Wavelet Transfrom; Djupinlärning; Ultraljud; Specklefiltrering; Medicinsk bildsegmentering; U-Net; Wavelet transformation;

    Abstract : Segmentation of ultrasonic images is a common task in healthcare that requires time and attention from healthcare professionals. Automation of medical image segmentation using deep learning solutions is fast growing field and has been shown to be capable of near human performance. READ MORE

  6. 5. Feature extraction from MEG data using self-supervised learning : Investigating contrastive representation learning methods to f ind informative representations

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Wilhelm Ågren; [2022]
    Keywords : Machine learning; Deep learning; Self-supervised learning; Cluster analysis; SimCLR; Magnetoencephalography; Partial sleep deprivation; Wavelet transform; Maskininlärning; Djupinlärning; Självövervakad inlärning; Klusteranalys; SimCLR; Magnetoencefalografi; Delvis sömndeprivering; Wavelet transform;

    Abstract : Modern day society is vastly complex, with information and data constantly being posted, shared, and collected everywhere. There is often an abundance of massive amounts of unlabeled data that can not be leveraged in a supervised machine learning context. READ MORE