Dynamic Range

Dynamic range, the ratio between the largest and smallest measurable values of a signal, is a critical parameter across diverse fields, impacting signal processing, image generation, and machine learning. Current research focuses on optimizing dynamic range for improved efficiency and accuracy in various applications, employing techniques like deep neural networks (particularly those incorporating state-space models), branch-and-bound algorithms, and adaptive compression methods tailored to specific noise conditions or data modalities. These advancements are crucial for enhancing the performance of real-time systems, improving the quality of HDR image and video generation, and enabling more robust and efficient machine learning models.