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Unbiased and Multilevel Methods for a Class of Diffusions Partially Observed via Marked Point Processes

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arXiv 2023年

作者： Alvarez, Miguel Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this article we consider the filtering problem associated to partially observed diffusions, with observations following a marked point process. In the model, the data form a point process with observation times that have its intensity driven by a diffusion, with the associated marks also depending upon the diffusion process. We assume that one must resort to time-discretizing the diffusion process and develop particle and multilevel particle filters to recursively approximate the filter. In particular, we prove that our multilevel particle filter can achieve a mean square error (MSE) of O(∈2) (∈ > 0 and arbitrary) with a cost of O(∈-2.5) versus using a particle filter which has a cost of O(∈-3) to achieve the same MSE. We then show how this methodology can be extended to give unbiased (that is with no time-discretization error) estimators of the filter, which are proved to have finite variance and with high-probability have finite cost. Finally, we extend our methodology to the problem of online static-parameter estimation. Key words: Unbiased Methods, Multilevel Monte Carlo, Non-Linear Filtering, Point Processes, Parameter *** Codes 60G55, 60G35, 62M20, 62F30 © 2023, CC BY.

关键词： Diffusion

Bayesian Parameter Inference for Partially Observed Stochastic Volterra Equations

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arXiv 2023年

作者： Jasra, Ajay Ruzayqat, Hamza Wu, Amin Applied Mathematics & Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this article we consider Bayesian parameter inference for a type of partially observed stochastic Volterra equation (SVE). SVEs are found in many areas such as physics and mathematical finance. In the latter field they can be used to represent long memory in unobserved volatility processes. In many cases of practical interest, SVEs must be time-discretized and then parameter inference is based upon the posterior associated to this time-discretized process. Based upon recent studies on time-discretization of SVEs (e.g. [24]) we use Euler-Maruyama methods for the afore-mentioned discretization. We then show how multilevel Markov chain Monte Carlo (MCMC) methods [19] can be applied in this context. In the examples we study, we give a proof that shows that the cost to achieve a 4 mean square error (MSE) of O(ϵ2), ϵ > 0, is O(ϵ− 4/2H+1 ), where H is the Hurst parameter. If one uses a single level MCMC method then the cost is O(ϵ−2(2H+3)/ 2H+1 ) to achieve the same MSE. We illustrate these results in the context of state-space and stochastic volatility models, with the latter applied to real *** Codes 62F15, 62M20, 60J10, 60J22, 65C40 © 2023, CC BY.

关键词： Mean square error

Stretchable Textile Bands for Ambulatory Electrocardiogram and Oximetry

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IEEE Journal on Flexible Electronics

IEEE Journal on Flexible Electronics 2022年第4期1卷 214-222页

作者： Liu, Jiaxi Le, Thy Sadatian, Ellie Yao, Lulu Garudadri, Harinath Dunphy, Stephen A. McClung, Christian Ng, Tse Nga University of California at San Diego Department of Electrical and Computer Engineering La Jolla CA92093 United States University of California at San Diego Materials Science and Engineering Program La Jolla CA92093 United States Qualcomm Institute University of California at San Diego La Jolla CA92093 United States Cb Innovations Llc Rancho Santa FeCA92067 United States

This work presents a vital sign monitoring interface combining electrocardiogram (ECG) and reflective photoplethysmography (PPG) acquisition on stretchable kinesiology tapes (KTs). The integrated textile bands are less prone to electrode misplacement and deliver high-quality diagnostic ECG signals with dry electrodes. The reflective PPG measured over the subclavian artery is used to track blood oxygen saturation, and in combination with ECG, enables the determination of pulse transit time and inference of blood pressure. This multimodal interface improves clinical workflows because it is easy to don, reduces motion artifacts, and facilitates more efficient and accurate diagnosis in emergency settings. © 2022 IEEE.

关键词： Electrocardiograms

STATISTICAL INFERENCE FOR GAUSSIAN WHITTLE-MATÉRN FIELDS ON METRIC GRAPHS

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arXiv 2023年

作者： Bolin, David Simas, Alexandre B. Wallin, Jonas Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Statistics Lund University Sweden

Whittle-Matérn fields are a recently introduced class of Gaussian processes on metric graphs, which are specified as solutions to a fractional-order stochastic differential equation. Unlike earlier covariance-based approaches for specifying Gaussian fields on metric graphs, the Whittle-Matérn fields are well-defined for any compact metric graph and can provide Gaussian processes with differentiable sample paths. We derive the main statistical properties of the model class, particularly the consistency and asymptotic normality of maximum likelihood estimators of model parameters and the necessary and sufficient conditions for asymptotic optimality properties of linear prediction based on the model with misspecified parameters. The covariance function of the Whittle-Matérn fields is generally unavailable in closed form, and they have therefore been challenging to use for statistical inference. However, we show that for specific values of the fractional exponent, when the fields have Markov properties, likelihood-based inference and spatial prediction can be performed exactly and computationally efficiently. This facilitates using the Whittle-Matérn fields in statistical applications involving big datasets without the need for any approximations. The methods are illustrated via an application to modeling of traffic data, where allowing for differentiable processes dramatically improves the *** Codes Primary 62M30, secondary 62M05, 60G60, 35R02 Copyright © 2023, The Authors. All rights reserved.

关键词： Gaussian distribution

External Lightning Protection System modeling on photovoltaic using ATP Draw

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External Lightning Protection System modeling on photovoltai...

International Conference on electrical engineering, computer Science and Informatics (EECSI)

作者： Rohana Rohana Surya Hardi Nasaruddin Nasaruddin Yuwaldi Away Doctoral Program. School of Engineering Universitas Syiah Kuala Banda Aceh Indonesia and Universitas Muhammadiyah Sumatera Utara Indonesia Dept. of Electrical Engineering Universitas Sumatera Utara Medan Indonesia Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Dept. of Electrical and Computer Universitas Syiah Kuala Banda Aceh Indonesia

Solar energy is environmentally friendly energy with a very large energy source. Indonesia is also exploring and implementing renewable energy options including solar panels as a viable and long-term alternative to green technology. On the other hand, to get sufficient solar radiation, solar panel systems are generally located in open areas such as hillsides, deserts, and water surfaces, making them more vulnerable to lightning strikes. Lightning is one of the main threats to PLTS, a lot of damage to solar panels is caused by lightning. Direct and indirect lightning strikes have great potential to affect the entire solar panel farm system. The main objective of this study is to evaluate Lightning Protection System (LPS) modeling for network-connected solar panel (PV) farm systems using the ATP-EMTP software. Field observations and simulation tests are used to determine the position of the LPS and its installation structure. The rolling ball method is used to see the installed LPS protection radius. The results show that it is necessary to add LPS to the PV field. It was found that there was one additional LPS needed on the north side of the PV field, because that position was not protected by the radius of the lightning rod. From the simulation results, it was found that the LPS installation structure was good, because the results from the modeling of the isolated LPS lightning protection system were better to use than without installing LPS.

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AV Navigation in 3D Urban Environments with Curriculum-based Deep Reinforcement Learning

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AV Navigation in 3D Urban Environments with Curriculum-based...

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Kevin Braathen de Carvalho Iure Rosa L. de Oliveira Alexandre S. Brandão Department of Electrical Engineering Graduate Program in Computer Science Nucleus of Specialization in Robotics Universidade Federal de Viçosa Viçosa MG Brazil Department of Electrical Engineering Federal University of Viçosa Viçosa MG Brazil

Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires robust and efficient decision-making algorithms. This paper presents a novel approach to UAV navigation in 3D environments using a Curriculum-based Deep Reinforcement Learning (DRL) approach. The proposed method utilizes a deep neural network to model the UAV’s decision-making process and to learn a mapping from the state space to the action space. The learning process is guided by a reinforcement signal that reflects the performance of the UAV in terms of reaching its target while avoiding obstacles and with energy efficiency. Simulation results show that the proposed method has a positive trade off when compared to the baseline algorithm. The proposed method was able to perform well in environments with a state space size of 22 millions, allowing the usage in big environments or in maps with high resolution. The results demonstrate the potential of DRL for enabling UAVs to operate effectively in complex environments.

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Joint Source Decomposition of Concurrent EEG-FMRI Data in Epilepsy and Control Groups 22

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Joint Source Decomposition of Concurrent EEG-FMRI Data in Ep...

22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Harding, J. Mason Pourmotabbed, Haatef Li, Yamin Rogge-Obando, Kimberly Wang, Kate Goodale, Sarah E. Wang, Shiyu Bibro, Camden Allee, Bergen Martin, Caroline Morgan, Victoria L. Englot, Dario J. Chang, Catie Departments of Electrical and Computer Engineering Vanderbilt University United States Departments of Biomedical Engineering Vanderbilt University United States Departments of Computer Science Vanderbilt University United States Neuroscience Graduate Program Vanderbilt University United States Departments of Radiology Vanderbilt University Medical Center United States Departments of Neurological Surgery Vanderbilt University Medical Center United States Vanderbilt Memory and Alzheimer's Center Vanderbilt University Medical Center United States

ISBN: (纸本)9798331520526

EEG and fMRI are complementary, noninvasive technologies for investigating human brain function. These modalities have been used to uncover large-scale functional networks and their disruptions in clinical populations. Given the high temporal resolution of EEG and high spatial resolution of fMRI, integrating these modalities can provide a more holistic understanding of brain activity. This work explores a multimodal source decomposition technique for extracting shared modes of temporal variation between fMRI BOLD signals and EEG spectral power fluctuations in the resting state. The resulting components are then compared between patients with focal epilepsy and controls, revealing multimodal network differences between groups. © 2025 IEEE.

关键词： Brain mapping

A Position Control System for a Single-port Laparoscopic Manipulating Robot

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A Position Control System for a Single-port Laparoscopic Man...

2022 International electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Amornthep Sonsilphong, Suphachoke Soemphol, Chaiyong Hormdee, Daranee Khampitak, Kovit Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Data Science Health Informatics Program Faculty of Medicine Khon Kaen Thailand Mahasarakham University Faculty of Engineering Department of Electrical Engineering Mahasarakham Thailand Khon Kaen University Embedded System RD Group Computer Engineering Faculty of Engineering Khon Kaen Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

The research herein proposes a position control system, designed for a single-port surgical robot, based on the lockup table method. The programmable logic controller (PLC) was implemented to move the single- port surgical robot and handle laparoscope and surgical instruments with feedback control. The output responses of the desired angle were investigated under several conditions. The rotating angle allows movement of the laparoscope in the range of -10o to +10o. The error of the desired position of the designed system was less than approximately ± 0.1o. Moreover, the output data from several experiments may be employed to improve the open-loop control systems. This system is also capable of providing computer vision task implementation, enabling semi- automatic or automatic surgery in the future. © 2022 IEEE.

关键词： Laparoscopy

Gradient Alignment with Prototype Feature for Fully Test-time Adaptation

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arXiv 2024年

作者： Shin, Juhyeon Lee, Jonghyun Lee, Saehyung Park, Minjun Lee, Dongjun Hwang, Uiwon Yoon, Sungroh Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Division of Digital Healthcare Yonsei University Korea Republic of

In context of Test-time Adaptation(TTA), we propose a regularizer, dubbed Gradient Alignment with Prototype feature (GAP), which alleviates the inappropriate guidance from entropy minimization loss from misclassified pseudo label. We developed a gradient alignment loss to precisely manage the adaptation process, ensuring that changes made for some data don’t negatively impact the model’s performance on other data. We introduce a prototype feature of a class as a proxy measure of the negative impact. To make GAP regularizer feasible under the TTA constraints, where model can only access test data without labels, we tailored its formula in two ways: approximating prototype features with weight vectors of the classifier, calculating gradient without back-propagation. We demonstrate GAP significantly improves TTA methods across various datasets, which proves its versatility and effectiveness. Copyright © 2024, The Authors. All rights reserved.

关键词： Alignment