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matlab fde12 solver  (MathWorks Inc)


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    MathWorks Inc matlab fde12 solver
    Matlab Fde12 Solver, 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/result/matlab fde12 solver/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab fde12 solver - by Bioz Stars, 2026-04
    90/100 stars

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    Comparison of computation time for the death-rate model with either a hyperbolic tangent \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\hat{H}}(t)$$\end{document} H ^ ( t ) function or a Heaviside H ( t ) function, and the impulsive (start/stop) model. Parameter fitting of the exponential growth model to patient 5 data was performed 100 times and the average total time and CPU time per fit are reported. Best-fitting parameters are also listed along with the frequency of occurrence (consensus)
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    Comparison of computation time for the death-rate model with either a hyperbolic tangent \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\hat{H}}(t)$$\end{document} H ^ ( t ) function or a Heaviside H ( t ) function, and the impulsive (start/stop) model. Parameter fitting of the exponential growth model to patient 5 data was performed 100 times and the average total time and CPU time per fit are reported. Best-fitting parameters are also listed along with the frequency of occurrence (consensus)
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    Average 90 stars, based on 1 article reviews
    fde12 solver - by Bioz Stars, 2026-04
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    Comparison of computation time for the death-rate model with either a hyperbolic tangent \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\hat{H}}(t)$$\end{document} H ^ ( t ) function or a Heaviside H ( t ) function, and the impulsive (start/stop) model. Parameter fitting of the exponential growth model to patient 5 data was performed 100 times and the average total time and CPU time per fit are reported. Best-fitting parameters are also listed along with the frequency of occurrence (consensus)

    Journal: Bulletin of Mathematical Biology

    Article Title: Modelling Radiation Cancer Treatment with a Death-Rate Term in Ordinary and Fractional Differential Equations

    doi: 10.1007/s11538-023-01139-2

    Figure Lengend Snippet: Comparison of computation time for the death-rate model with either a hyperbolic tangent \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\hat{H}}(t)$$\end{document} H ^ ( t ) function or a Heaviside H ( t ) function, and the impulsive (start/stop) model. Parameter fitting of the exponential growth model to patient 5 data was performed 100 times and the average total time and CPU time per fit are reported. Best-fitting parameters are also listed along with the frequency of occurrence (consensus)

    Article Snippet: To numerically simulate both ODE and FDE models, we use the same solver for consistency, namely the FDE solver fde12 in MATLAB (Garrappa ), which implements a predictor–corrector algorithm (Diethelm et al. ).

    Techniques: Comparison