Abstract
The extraction of interesting information from enormous and irregular datasets has always been a significant research topic. For the datasets with irregular distribution and self-similarity, multifractal theory is the most appreciated approach and has been successfully applied in many fields, such as financial analysis, image processing, medical diagnosis, earthquake study, etc. In this paper, we make a detailed analysis and summary on three main functions, namely multifractal structure diagnosis, tendency and singularity analysis. Finally, some experiments based on oil prices data and spatial physical data are carried out to validate its performance effectively.
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