Dear colleagues,
Applied mathematics and statistics methods have advanced considerably during the past decades, mainly as a result of the remarkable rise of computing and data abundance. Statistical process monitoring involves collecting data, learning from it, and developing data-driven models for monitoring purposes. Wavelet methods have become standard in applied mathematics and an effective tool for statistical monitoring, including dimension reduction, denoising, feature engineering for machine learning methods, time-frequency analysis, image processing, and signal processing. This Special Issue seeks new techniques and innovative applications in different statistical process monitoring settings, including in the fields of health monitoring, image monitoring, and profile monitoring, to name a few.
More information: https://www.mdpi.com/si/mathematics/0MT0ILZ919
Best,
Achraf
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Achraf Cohen, Ph.D.
Assistant Professor
Statistics and Data Science
The University of West Florida
https://pages.uwf.edu/acohenhttps://acohenstat.github.io/------------------------------