Abstract: This paper introduces an innovative approach utilizing a deep neural network (DNN) to optimize the modulation scheme for time-modulated antenna array (TMAA) to verify specific side lobe and ...

Six-month, CTEL-led programme blends machine learning, deep learning and generative AI with hands-on projects and a three-day ...

Abstract: Deep neural networks (DNNs) and especially convolutional neural networks (CNNs) have revolutionized the way we approach the analysis of large quantities of data. However, the largely ad hoc ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Since the rise of molecular high-throughput technologies, many diseases are now studied on multiple omics layers in parallel. Understanding the interplay between microRNAs (miRNA) and their target ...

ABSTRACT: An algorithm is being developed to conduct a computational experiment to study the dynamics of random processes in an asymmetric Markov chain with eight discrete states and continuous time.

Continual learning (CL), the ability to learn new tasks without forgetting existing ones, is one of the greatest challenges in AI. Our work provides an analytically tractable theory that captures some ...

There was an error while loading. Please reload this page. Abstract: In this tutorial we will introduce software defined radios (SDR) and explore the application of ...