A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

SoftBank announced that it has successfully achieved radio signal processing using Massive MIMO and demonstrated 16-layer MU-MIMO (Multi-User Multiple Input Multiple Output) downlink (DL) in an ...

Introduction: Brain-computer interfaces (BCIs) leverage EEG signal processing to enable human-machine communication and have broad application potential. However, existing deep learning-based BCI ...

Introduction: Large language models are capable of summarizing research, supporting clinical reasoning, and engaging in coherent conversations. However, their inputs are limited to user-generated text ...

Noise is the bane of signal engineers, but deep learning models with AI can adapt to specific noises and filter them out with minimal to no human intervention required. It is a powerful feature for ...

Running Python scripts is one of the most common tasks in automation. However, managing dependencies across different systems can be challenging. That’s where Docker comes in. Docker lets you package ...

SynapDrive-AI simulates seamless Brain-Computer Interface integration with modular AGI for real-time, safe control of advanced physical systems like Tesla vehicles, SpaceX rockets, and Hyperloop ...

ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...

Artificial Intelligence (AI), especially deep learning, has significantly impacted audio and video signal processing. With large-scale multimodal datasets and enhanced computational resources, AI is ...