Essays about: "continuous Markov model"

Showing result 1 - 5 of 21 essays containing the words continuous Markov model.

1. 1. 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

3. 2. Cost Analysis of Levodopa Micro Tablet Dispenser for Treatment of Parkinson's Disease

   University essay from KTH/Matematisk statistik

   Author : Alexander Larsson; Anna Söderbärg; [2023]
   Keywords : Parkinson s disease; MDS-UPDRS; quality-adjusted life year; incremental cost-effectiveness ratio; Markov chain; Markov model; micro tablet dispenser; levodopa; Parkinsons sjukdom; MDS-UPDRS; kvalitetsjusterade levnadsår; inkrementell kostnadseffektivitetskvot; Markovkedja; Markovmodell; mikrotablettdispenser; levodopa;

   Abstract : Parkinson's is a chronic, progressive, neurodegenerative disease. The most common treatment is levodopa/carbidopa, which suppresses the symptoms of the disease. In this report, a cost-utility analysis of the MyFID levodopa/carbidopa micro tablet dispenser has been conducted. READ MORE

4. 3. Energy Sustainable Reinforcement Learning-based Adaptive Duty-Cycling in Wireless Sensor Networks-based Internet of Things Networks

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Nadia Charef; [2023]
   Keywords : Reinforcement Learning; Q-learning; Dynamic Energy Management; Energy Sustainabiltiy; IEEE802.15.4 MAC Protocol; Adaptive Duty Cycling; Wireless Sensors Networks; Internet of Things;

   Abstract : The Internet of Things (IoT) is widely adopted across various fields due to its flexibility and low cost. Energy-harvesting Wireless Sensor Networks (WSNs) are becoming a building block of many IoT applications and provide a perpetual source of energy to power energy-constrained IoT devices. READ MORE

5. 4. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation

   University essay from Lunds universitet/Matematisk statistik

   Author : Mika Persson; [2022]
   Keywords : Bayesian Statistics; Deep Learning; Frequency Estimation; Generative Adversarial Networks; Artificial Neural Networks; Statistical Modelling; Mathematics and Statistics;

   Abstract : The Discrete Fourier Transform is the simplest way to obtain the spectrum of a discrete complex signal. This thesis concerns the case when the signal is known to contain a small (unknown) number of frequencies, not limited to the discrete Fourier frequencies, embedded in complex Gaussian noise. READ MORE

6. 5. Spatial Statistical Modelling of Insurance Claim Frequency

   University essay from Lunds universitet/Matematisk statistik

   Author : Daniel Faller; [2022]
   Keywords : Insurance risk; claim frequency; Markov chain Monte Carlo MCMC ; Riemann manifold Metropolis adjusted Langevin algorithm MMALA ; spatial statistics; Gaussian Markov random field GMRF ; preconditioned Crank Nicolson Langevin algorithm pCNL ; Gibbs sampling; Bayesian hierarchical modelling; high dimensional; shrinkage prior; horseshoe prior; regularisation.; Mathematics and Statistics;

   Abstract : In this thesis a fully Bayesian hierarchical model that estimates the number of aggregated insurance claims per year for non-life insurances is constructed using Markov chain Monte Carlo based inference with Riemannian Langevin diffusion. Some versions of the model incorporate a spatial effect, viewed as the relative spatial insurance risk that originates from a policyholder's geographical location and where the relative spatial insurance risk is modelled as a continuous spatial field. READ MORE