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monofractal dfa implemented in  (MathWorks Inc)


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    MathWorks Inc monofractal dfa implemented in
    Example of <t>multifractal</t> spectrum that is produced from multifractal <t>DFA.</t> Note the monofractal signal produces a very narrow spectrum, indicating monofractal scaling is present and monofractal DFA is sufficient to characterize the scaling and correlation properties of the signal.
    Monofractal Dfa Implemented In, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/monofractal+dfa+implemented+in/pmc03876327-147-7-11?v=MathWorks+Inc
    Average 90 stars, based on 1 article reviews
    monofractal dfa implemented in - by Bioz Stars, 2026-07
    90/100 stars

    Images

    1) Product Images from "Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods"

    Article Title: Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

    Journal: Journal of Diabetes Science and Technology

    doi:

    Example of multifractal spectrum that is produced from multifractal DFA. Note the monofractal signal produces a very narrow spectrum, indicating monofractal scaling is present and monofractal DFA is sufficient to characterize the scaling and correlation properties of the signal.
    Figure Legend Snippet: Example of multifractal spectrum that is produced from multifractal DFA. Note the monofractal signal produces a very narrow spectrum, indicating monofractal scaling is present and monofractal DFA is sufficient to characterize the scaling and correlation properties of the signal.

    Techniques Used: Produced

    Results from Monofractal Detrended Fluctuation Analysis of Sensor Glucose and ISIG Data Over Cohort
    Figure Legend Snippet: Results from Monofractal Detrended Fluctuation Analysis of Sensor Glucose and ISIG Data Over Cohort

    Techniques Used:

    Multifractal spectrums comparing CGM device types and sensor locations. The plots on the left were created using SG data, and the plots on the right were created using ISIG data.
    Figure Legend Snippet: Multifractal spectrums comparing CGM device types and sensor locations. The plots on the left were created using SG data, and the plots on the right were created using ISIG data.

    Techniques Used:

    Multifractal spectrum comparison for data sets that had the same scaling exponent from monofractal DFA.
    Figure Legend Snippet: Multifractal spectrum comparison for data sets that had the same scaling exponent from monofractal DFA.

    Techniques Used: Comparison

    (A) This example shows good agreement between SG data for each of the three CGM devices, but the multifractal spectrums for each data set are quite different. (B) This example shows average agreement between SG data for two CGM devices, but the multifractal spectrums for each data set overlap.
    Figure Legend Snippet: (A) This example shows good agreement between SG data for each of the three CGM devices, but the multifractal spectrums for each data set are quite different. (B) This example shows average agreement between SG data for two CGM devices, but the multifractal spectrums for each data set overlap.

    Techniques Used:



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    monofractal dfa implemented in  (MathWorks Inc)
    90
    MathWorks Inc monofractal dfa implemented in
    Example of <t>multifractal</t> spectrum that is produced from multifractal <t>DFA.</t> Note the monofractal signal produces a very narrow spectrum, indicating monofractal scaling is present and monofractal DFA is sufficient to characterize the scaling and correlation properties of the signal.
    Monofractal Dfa Implemented In, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/monofractal+dfa+implemented+in/pmc03876327-147-7-11?v=MathWorks+Inc
    Average 90 stars, based on 1 article reviews
    monofractal dfa implemented in - by Bioz Stars, 2026-07
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Example of multifractal spectrum that is produced from multifractal DFA. Note the monofractal signal produces a very narrow spectrum, indicating monofractal scaling is present and monofractal DFA is sufficient to characterize the scaling and correlation properties of the signal.

    Journal: Journal of Diabetes Science and Technology

    Article Title: Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

    doi:

    Figure Lengend Snippet: Example of multifractal spectrum that is produced from multifractal DFA. Note the monofractal signal produces a very narrow spectrum, indicating monofractal scaling is present and monofractal DFA is sufficient to characterize the scaling and correlation properties of the signal.

    Article Snippet: This study uses both monofractal DFA and multifractal DFA implemented in MATLAB (Mathworks, Natick, MA) based on the descriptions provided by Ihlen 32 and Kantelhardt and coauthors.

    Techniques: Produced

    Results from Monofractal Detrended Fluctuation Analysis of Sensor Glucose and ISIG Data Over Cohort

    Journal: Journal of Diabetes Science and Technology

    Article Title: Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

    doi:

    Figure Lengend Snippet: Results from Monofractal Detrended Fluctuation Analysis of Sensor Glucose and ISIG Data Over Cohort

    Article Snippet: This study uses both monofractal DFA and multifractal DFA implemented in MATLAB (Mathworks, Natick, MA) based on the descriptions provided by Ihlen 32 and Kantelhardt and coauthors.

    Techniques:

    Multifractal spectrums comparing CGM device types and sensor locations. The plots on the left were created using SG data, and the plots on the right were created using ISIG data.

    Journal: Journal of Diabetes Science and Technology

    Article Title: Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

    doi:

    Figure Lengend Snippet: Multifractal spectrums comparing CGM device types and sensor locations. The plots on the left were created using SG data, and the plots on the right were created using ISIG data.

    Article Snippet: This study uses both monofractal DFA and multifractal DFA implemented in MATLAB (Mathworks, Natick, MA) based on the descriptions provided by Ihlen 32 and Kantelhardt and coauthors.

    Techniques:

    Multifractal spectrum comparison for data sets that had the same scaling exponent from monofractal DFA.

    Journal: Journal of Diabetes Science and Technology

    Article Title: Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

    doi:

    Figure Lengend Snippet: Multifractal spectrum comparison for data sets that had the same scaling exponent from monofractal DFA.

    Article Snippet: This study uses both monofractal DFA and multifractal DFA implemented in MATLAB (Mathworks, Natick, MA) based on the descriptions provided by Ihlen 32 and Kantelhardt and coauthors.

    Techniques: Comparison

    (A) This example shows good agreement between SG data for each of the three CGM devices, but the multifractal spectrums for each data set are quite different. (B) This example shows average agreement between SG data for two CGM devices, but the multifractal spectrums for each data set overlap.

    Journal: Journal of Diabetes Science and Technology

    Article Title: Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: Continuous Glucose Monitoring Devices, Sensor Locations, and Detrended Fluctuation Analysis Methods

    doi:

    Figure Lengend Snippet: (A) This example shows good agreement between SG data for each of the three CGM devices, but the multifractal spectrums for each data set are quite different. (B) This example shows average agreement between SG data for two CGM devices, but the multifractal spectrums for each data set overlap.

    Article Snippet: This study uses both monofractal DFA and multifractal DFA implemented in MATLAB (Mathworks, Natick, MA) based on the descriptions provided by Ihlen 32 and Kantelhardt and coauthors.

    Techniques: