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non-linear least-squares algorithm matlab software version 9.5.0.1067069 (r2018b) update 4  (MathWorks Inc)


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    MathWorks Inc non-linear least-squares algorithm matlab software version 9.5.0.1067069 (r2018b) update 4
    Non Linear Least Squares Algorithm Matlab Software Version 9.5.0.1067069 (R2018b) Update 4, 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/non-linear+least+squares+algorithm/bio_rxiv__2025__05__02__651947-136-31-35
    Average 90 stars, based on 1 article reviews
    non-linear least-squares algorithm matlab software version 9.5.0.1067069 (r2018b) update 4 - by Bioz Stars, 2026-11
    90/100 stars

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    Article Title: A Spectral Demixing Model for Triplex In Vivo Imaging of Optical Coherence Tomography Contrast Agents
    Article Snippet: The non-linear least squares algorithm is run using the function lsqnonneg in MATLAB 2019a.

    Article Title: Frequency shifts of free water signals from compact bone: Simulations and measurements using a UTE-FID sequence.
    Article Snippet: 1Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany 2Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz, Center Munich at the University of Tübingen, Tübingen, Germany 3German Center for Diabetes Research (DZD), Tübingen, Germany 4Karlsruhe Institute of Technology, Institute of Mechanical Process Engineering and Mechanics, Karlsruhe, Germany

    Article Title: Model-Predicted Balance Between Neural Excitation and Inhibition Was Maintained Despite of Age-Related Decline in Sensory Evoked Local Field Potential in Rat Barrel Cortex
    Article Snippet: Seven model parameters were optimized ( ) using a non-linear least squares algorithm (Levenberg–Marquardt algorithm, Matlab function “lsqnonlin”) for each animal to fit the mean evoked LFP time series during the time period 0 ≤ t ≤ 200 ms. Excitatory and inhibitory components of the LFP were then estimated from the model using the optimized parameters.

    Article Title: Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study
    Article Snippet: Metabolite signal decays as a function of b -value were then fitted using two different approaches, using a non-linear least squares algorithm in MATLAB ( fit function, Trust-Region method): First, Callaghan’s model of randomly oriented sticks ( ) (mimicking neurites or processes) with metabolite diffusivity D intra along the neurite/process: (1) S S 0 = π 4 b D intra e r f b D intra Second, the cumulant expansion at second order: (2) ln S S 0 = − b D + 1 6 b D 2 K Yielding the apparent diffusion coefficient D and kurtosis K, where b refers to the b -value and erf refers to the error function.

    Article Title: Dimerization of the Trk receptors in the plasma membrane: effects of their cognate ligands
    Article Snippet: We then fit a monomer-dimer model to the corrected E D data while varying K diss and E ̃ , using a MATLAB non-linear least squares algorithm to find the best-fit values of K diss and E ̃ and their 66% confidence intervals.

    Article Title: Shifted-excitation rotational Raman spectroscopy and Bayesian inference for in situ temperature and composition determination in laminar flames
    Article Snippet: Performing the weighted least-square minimization (here: MATLAB non-linear least squares algorithm) considering the measured data and the prior information, the point estimate obtained is called the maximum a-posteriori-estimate (MAP) x MAP .

    Article Title: Identification of species from visible and near-infrared spectral emission of a nitromethane-air diffusion flame
    Article Snippet: Both gray body functional forms for various temperatures were fitted to the experimental data with the spectral bands removed using a non-linear least squares algorithm in MatLab.

    Imaging:

    Article Title: Analysis of physiological noise in quantitative cardiac magnetic resonance
    Article Snippet: .. The SNR and TSNR for each of the 24 individual imaging parameters were averaged across the four subjects, and fit to the PNC model of using a non-linear least squares algorithm provided by Matlab to estimate the physiological noise scaling parameter, λ and physiological coil covariance parameter, α . ..



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