An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

In the previous chapter, we learned various strategies to guide AI models 'down the mountain' (optimization algorithms), such ...

A highly regarded research direction is “Physical Neural Networks” (PNNs), which utilize physical systems like light, ...

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

Objective This study aimed to leverage machine learning algorithms to explore the relationship between anti-double-stranded DNA (anti-dsDNA) immunoglobulin G (IgG) glycosylation and the degree of ...

Abstract: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...

Abstract: Motivated by the growing use of Artificial intelligence (AI) tools in control design, this paper takes steps toward bridging results from Direct Gradient methods for the Linear Quadratic ...