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High-Resolution Noisy Signal and Image Processing

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Title: High-Resolution Noisy Signal and Image Processing
Description: 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.
Authors: Edward Valachovic, Author, Mingzeng Sun, Author, Barry Loneck, Author, Amy Potrzeba-Macrina, Author, Devin Smith, Author, Igor Zurbenko, Author
Resource Type: eBook.
Subjects: Signal processing
Categories: TECHNOLOGY & ENGINEERING / Signals & Signal Processing, COMPUTERS / Image Processing, SCIENCE / Earth Sciences / Meteorology & Climatology
Database: eBook Collection (EBSCOhost)
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 2739638
RelevancyScore: 1103
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1103.19409179688
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  Data: High-Resolution Noisy Signal and Image Processing
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  Data: 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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      – Code: 621.3822
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Signal processing
        Type: general
    Titles:
      – TitleFull: High-Resolution Noisy Signal and Image Processing
        Type: main
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            NameFull: Edward Valachovic, Author
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            NameFull: Mingzeng Sun, Author
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            NameFull: Igor Zurbenko, Author
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            NameFull: Edward Valachovic, Author
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            NameFull: Mingzeng Sun, Author
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            NameFull: Barry Loneck, Author
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            NameFull: Amy Potrzeba-Macrina, Author
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            NameFull: Devin Smith, Author
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
            – D: 06
              M: 03
              Type: profile
              Y: 2021
          Identifiers:
            – Type: isbn-print
              Value: 9781527562936
            – Type: isbn-electronic
              Value: 9781527564169
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            – TitleFull: High-Resolution Noisy Signal and Image Processing
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