As AI models move from design to production, mining engineers face a double-faceted challenge: delivering real-time performance on embedded devices with ...

Many controlled processes, such as biochemical ones, are repetitive, similar to batch-organized processes. They generate Optimal Control Problems (OCPs) solved by optimal controllers, which often ...

A key challenge for systems neuroscience is to understand the coexistence of robustness and sensitivity in neural networks. In particular, a neural system must be robust against perturbations to its ...

During the recent decade, deep learning technology, particularly deep neural network (DNN), has gained tremendous popularity in various fields including signal processing (SP). As a data-driven ...

MATLAB (short for Matrix Laboratory) is a powerful software tool used for technical computing and visualization. It is widely used in a variety of fields, including engineering, science, finance, and ...

This teaching package contains modular contents for the introduction of the fundamentals of Neural Networks. The package consists of a series of MATLAB Live Scripts with complementary PowerPoint ...

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: Since the outbreak of the COVID-19 virus, various technologies have developed as an alternative to preventing the spread of the COVID-19 virus; one of them is face mask detection. Many ...

Abstract: In modern control theory, there are several variations to different controller designs. The same can be said for Neural Network (NN) Controllers. The goal of this paper is to implement a ...

TensorFlow is an open-source framework developed by Google scientists and engineers for numerical computing. TensorFlow.NET is a library that provides a .NET Standard binding for TensorFlow, allowing ...