Fractal Structure

Fractal structures, characterized by self-similarity across multiple scales, are being actively investigated for their applications in diverse fields. Current research focuses on leveraging fractal properties in areas such as optimization algorithms (e.g., using Hilbert curves for efficient sampling), neural network training (analyzing fractal boundaries in hyperparameter spaces), and image processing (employing fractal scanning for improved state space models and generating fractal datasets for anomaly detection). These studies highlight the potential of fractal geometry to improve the efficiency and performance of various computational methods and offer new approaches to data analysis and machine learning.