Prospects for the Application of Signal Detection and Processing Technologies in the Era of Artificial Intelligence

Abstract

With the rapid advancement of artificial intelligence, the traditional discipline of signal detection and processing is undergoing profound transformation and encountering broad opportunities. This paper aims to explore the fundamental connotations, current development status, core points of integration, typical application scenarios, as well as future challenges and prospects of signal detection and processing technologies in the context of the AI era. The article points out that traditional signal processing relies on mathematical models and prior knowledge, whereas artificial intelligence, particularly deep learning, with its powerful feature extraction and nonlinear mapping capabilities, is reshaping the paradigm of signal processing. From intelligent voice assistants and predictive maintenance in industry to biomedical diagnostics and autonomous driving, the deep integration of these two fields not only enhances the precision and efficiency of signal processing but also opens up entirely new application domains. Finally, this paper analyzes the challenges currently faced by technological integration and looks ahead to future trends toward explainability, lightweight deployment, and multimodal collaboration.