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fmincon nonlinear least-squares fitting function  (MathWorks Inc)


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    MathWorks Inc fmincon nonlinear least-squares fitting function
    Fmincon Nonlinear Least Squares Fitting Function, 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/function+fmincon/us12359340-367-11-15
    Average 90 stars, based on 1 article reviews
    fmincon nonlinear least-squares fitting function - by Bioz Stars, 2026-11
    90/100 stars

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    Article Title: Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks.
    Article Snippet: We used the fit nonlinear least squares fitting function in Matlab R2019b.

    Article Title: Modeling the kinetics of heteromeric potassium channels
    Article Snippet: This was done by taking Equation (15) with parameters from Al-Sabi et al. , and using the MATLAB nonlinear least squares fitting function to find the best fitting function of the form P o p e n ( V ) 4 .

    Article Title: A flexible capacitive photoreceptor for the biomimetic retina
    Article Snippet: Nonlinear least-squares fitting function in MATLAB was used to model identification where the loss function is defined to minimize L 2 norm of the relative error of the real and the imaginary parts of the admittance over the frequency range.

    Article Title: Kinetic model for molecular beam epitaxy growth of III-V bismide alloys
    Article Snippet: Fitting to the mole fractions is accomplished using the fmincon nonlinear least-squares fitting function in MATLAB R2020a.29 The objective function to be minimized by fmincon is the squared error between measured and modeled group-V mole fractions, weighted by the uncertainty in each measured group-V mole fraction χ 2 = χ B i 2 + χ Sb 2 + χ A s 2 = ∑ i = 1 N [ ( x i - x ˆ i ) 2 σ Bi , i 2 + ( y i - y ˆ i ) 2 σ Sb , i 2 + ( z i - z ˆ i ) 2 σ As , i 2 ] , ( 9 ) where xi, yi, and zi are the measured Bi, Sb, and As mole fractions for the i-th sample, {circumflex over (x)}i, ŷi, and {circumflex over (z)}i are the modeled Bi, Sb, and As mole fractions, and σBi,i, σSb,i, and σAs,i are the Bi, Sb, and As mole fraction uncertainties reported in Table II.

    Article Title: Determination and discussion of apparent reaction kinetics of liquid diacyl peroxide synthesis in a microreactor
    Article Snippet: Organic peroxides are highly reactive and hazardous substances requiring extra care during their synthesis and handling, especially the exothermic peroxidation reaction.. In our previous study, efficient and safe synthesis of di-(3,5,5-trimethylhexanoyl) peroxide was realized by exploiting microreaction technology.. For better understanding and guidance of the process, the apparent reaction kinetics of its synthesis in a microreactor is determined herein.

    Article Title: Theory of structural relaxation in glass from the thermodynamics of irreversible processes
    Article Snippet: This work proposes a fundamental thermodynamic description of structural relaxation in glasses by establishing a link between the Prony series solution to volume relaxation derived from the principles of irreversible thermodynamics and asymmetric Lévy stable distribution of relaxation rates.. Additionally, it is shown that the bulk viscosity of glass, and not the shear viscosity, is the transport coefficient governing structural relaxation.. We also report the distribution of relaxation times and energy barrier heights underpinning stretched exponential relaxation.

    Article Title: Three-dimensional tracking using a single-spot rotating point spread function created by a multiring spiral phase plate
    Article Snippet: A nonlinear least-squares fitting function in MATLAB was used to generate the best fitting parameters, namely the x - y location that gave the maximum cross-correlation.

    Diffusion-based Assay:

    Article Title: The Costs of Close Contacts: Visualizing the Energy Landscape of Cell Contacts at the Nanoscale
    Article Snippet: .. JD distributions were fitted to the probability distribution function P ( r 2 , Δt ) = 1 − exp ( r 2 / r 0 2 ( t ) ) , where r 0 2 ( t ) = 4 Dt + 4 σ 2 , of a particle with a diffusion coefficient D and localization precision σ to be within the radius r of a shell at a time Δt ( ) using a MATLAB built-in nonlinear least-squares fitting function, yielding r 0 2 . ..



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