Abstract: We report a newly developed room-temperature (RT) shimming method for high-temperature superconducting (HTS) magnets employing a deep Q-network (DQN), a type of reinforcement learning theory ...
This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...
Python and MATLAB are valuable for an electrical engineer's career, but the better choice depends on your field, industry, and career goals. Electrical engineers face many challenges: dealing with ...
Human inventions, namely engineered systems, have relied on fundamental discoveries in physics and mathematics, e.g., Maxwell’s equations, Quantum mechanics, Information theory, etc., thereby applying ...
A neural network was trained to accurately predict the entire single-event specific energy spectra for use in alpha-particle microdosimetry calculations. Microdosimetry considers the stochastic nature ...
Abstract: Deep learning techniques are empowering many space based applications with good speed and accuracy. The application includes categorizing astronomical data, identifying celestial bodies, ...
This demo shows how to use transformer networks to model the daily prices of stocks in MATLAB®. We will predict the price trends of three individual stocks and use the predicted time series values to ...
MathWorks has unveiled Release 2022b (R2022b) of the MATLAB and Simulink product families. R2022b introduces two new products and several enhanced features that simplify and automate Model-Based ...
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