Multiband Signal Fusion

Multiband signal fusion integrates data from multiple frequency bands to improve the quality and resolution of signals in various applications, such as imaging and speech enhancement. Current research emphasizes hybrid approaches combining traditional signal processing with deep learning models, including convolutional neural networks and vision transformers, to achieve superior performance compared to using either method alone. This fusion technique is particularly valuable in scenarios where high-bandwidth systems are impractical, enabling advancements in areas like high-resolution radar imaging, improving the accuracy of object detection and classification, and enhancing speech quality in noisy environments.