As AI models move from design to production, mining engineers face a double-faceted challenge: delivering real-time performance on embedded devices with ...
MathWorks is integrating modern AI coding agents with its traditional engineering software, MATLAB. This move surprised many users due to the generational difference between the platforms. MATLAB and ...
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 ...
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 ...
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 ...
Design Space Exploration for Edge Machine Learning Featured by MathWorks FPGA DL Processor: A Survey
Abstract: This paper proposes a Design Space Exploration for Edge machine learning through the utilization of the novel MathWorks FPGA Deep Learning Processor IP, featured in the HDL Deep Learning ...
Optimization of pattern-synthesis algorithms. Applying a deep-learning network to generate antenna element weights. Using a convolution neural network to perform pattern synthesis with deep learning.
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