Active Noise Control

Active noise control (ANC) aims to reduce unwanted noise using opposing sound waves, with current research heavily focused on improving its efficiency and applicability in diverse settings. This involves developing computationally efficient algorithms, such as adaptive filtering techniques (e.g., filtered-x least mean squares) and deep learning models (e.g., convolutional neural networks), often tailored for specific hardware constraints (e.g., mobile devices) and noise characteristics (e.g., low-frequency noise). Significant advancements are being made in areas like portable ANC devices for construction sites and improved speech enhancement in noisy environments for earbuds, highlighting the technology's growing impact on both industrial noise mitigation and consumer electronics.