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High-Resolution Noisy Signal and Image Processing
Amy Potrzeba-Macrina , Barry Loneck , Devin Smith , Edward Valachovic , Igor Zurbenko , Mingzeng Sun
The book introduces valuable new data analysis methods in time and space, and provides many examples and recommendations for new developments. It will teach the reader how to use powerful, but very flexible, tools, frequently referred to as Kolmogorov-Zurbenko Filters. The main construction of these tools is derived from spectral concepts where natural laws occur. Rather than forcing models on data, they allow us to discover the nature of phenomena hidden within the data. The methods outlined here are capable of obtaining accurate results within very noisy environments. Their extremely accurate spectral diagnostics permits the separation of different sources of influences within the data. Treating each source separately can achieve highly accurate explanations of the total picture. For example, this approach is able to identify the most dangerous moments and locations for hurricanes and tornados.
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