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matlab's least squares fitting algorithm  (MathWorks Inc)


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    MathWorks Inc matlab's least squares fitting algorithm
    Matlab's Least Squares Fitting Algorithm, 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/least-square+algorithm+matlab/pm39004838-83-26-24
    Average 90 stars, based on 1 article reviews
    matlab's least squares fitting algorithm - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: A mathematical modeling study of the effectiveness of contact tracing in reducing the spread of infectious diseases with incubation period.
    Article Snippet: https://doi.org/10.1016/j.mbs.2025.109415 Received 21 November 2024; Received in revised form 11 February 2025; Accepte vailable online 26 February 2025 025-5564/© 2025 Elsevier Inc. All rights are reserved, including those for text and d 21 February 2025 data mining, AI training, and similar technologies.. M. Ladib et al. a t p t t E r i o i 1 i t w I w a t S t o w m a r o e w c c s t a s w f G t a i h p t t e r b i c a p c a d p c

    Article Title: Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing.
    Article Snippet: 1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, School of Electronic Science and Engineering, National Model Microelectronics College, Xiamen University, Xiamen, China 2Institute of Artificial Intelligence, Xiamen University, Xiamen, China 3Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China 4Clinical & Technical Supports, Philips Healthcare, Beijing, China 5Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China 6Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China

    Article Title: Method for Extracellular Electrochemical Impedance Spectroscopy on Epithelial Cell Monolayers
    Article Snippet: In the past, we used the L2 norm of the residual (resnorm) [1] as a reasonable error metric reported from MATLAB’s nonlinear least squares fitting algorithm.

    Article Title: Conformational trajectory of the HIV-1 fusion peptide during CD4-induced envelope opening.
    Article Snippet: FRET histograms (conformational distributions) were presented as mean ± s.e.m. and fitted into a sum of three distinct Gaussian/Normal distributions using the least-squares fitting algorithm in MATLAB.

    Article Title: Method for Extracellular Electrochemical Impedance Spectroscopy on Epithelial Cell Monolayers
    Article Snippet: In the past, we used the L 2 norm of the residual (resnorm) [1] as a reasonable error metric reported from MATLAB’s nonlinear least squares fitting algorithm.

    Article Title: HIV-1-envelope trimer transitions from prefusion-closed to CD4-bound-open conformations through an occluded-intermediate state
    Article Snippet: FRET histograms were presented as mean ± s.e.m. and fitted into a sum of three or four distinct Gaussian/normal N ( μ , σ 2 ) distributions using the least-squares fitting algorithm in MATLAB.

    Article Title: Optimizing pseudo-spiral sampling for abdominal DCE MRI using a digital anthropomorphic phantom.
    Article Snippet: The extended Tofts model was fitted to the reconstructed data for 50 random voxels per simulated organ (liver, spleen, pancreas, and pancreatic tumor) using MATLAB’s least squares fitting algorithm with default settings.

    Binding Assay:

    Article Title: Bulk-level maps of pioneer factor binding dynamics during Drosophila maternal-to-zygotic transition.
    Article Snippet: .. The equation was solved and adjustable parameters (dissociation constant and binding site concentrations) were determined using the least-squares fitting algorithm, lsqcurvefit, and the global optimization solver, MultiStart in Matlab. ..



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    MathWorks Inc nonnegative linear least-squares spectral unmixing algorithm matlab isqnonneg
    SRS spectra of cholesterol crystal, saturated CE, unsaturated CE, and TAG in the C–H region (a) and fingerprint region (b). Shaded lines: main spectral differences between saturated CE (green) and unsaturated CE (blue). (c) Ternary plot of the calculated fractions of three-component mixtures using SRS imaging and the spectral <t>unmixing</t> algorithm. Black circles: lipid standard mixture fractions. Red dots: calculated lipid fractions.
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    MathWorks Inc least-squares algorithms built into matlab r2022b
    SRS spectra of cholesterol crystal, saturated CE, unsaturated CE, and TAG in the C–H region (a) and fingerprint region (b). Shaded lines: main spectral differences between saturated CE (green) and unsaturated CE (blue). (c) Ternary plot of the calculated fractions of three-component mixtures using SRS imaging and the spectral <t>unmixing</t> algorithm. Black circles: lipid standard mixture fractions. Red dots: calculated lipid fractions.
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    Image Search Results


    SRS spectra of cholesterol crystal, saturated CE, unsaturated CE, and TAG in the C–H region (a) and fingerprint region (b). Shaded lines: main spectral differences between saturated CE (green) and unsaturated CE (blue). (c) Ternary plot of the calculated fractions of three-component mixtures using SRS imaging and the spectral unmixing algorithm. Black circles: lipid standard mixture fractions. Red dots: calculated lipid fractions.

    Journal: Journal of Biomedical Optics

    Article Title: Discrimination of lipid composition and cellular localization in human liver tissues by stimulated Raman scattering microscopy

    doi: 10.1117/1.JBO.29.1.016008

    Figure Lengend Snippet: SRS spectra of cholesterol crystal, saturated CE, unsaturated CE, and TAG in the C–H region (a) and fingerprint region (b). Shaded lines: main spectral differences between saturated CE (green) and unsaturated CE (blue). (c) Ternary plot of the calculated fractions of three-component mixtures using SRS imaging and the spectral unmixing algorithm. Black circles: lipid standard mixture fractions. Red dots: calculated lipid fractions.

    Article Snippet: A nonnegative linear least-squares spectral unmixing algorithm (MATLAB Isqnonneg) was applied to both the C–H and the fingerprint region spectra for spectral unmixing of each pixel in lipid droplets.

    Techniques: Imaging

    Schematic diagram of the image analysis pipeline and representative SRS images and lipid composition maps of a liver tissue section from a patient with NASH. From the SRS images at 2850 (a) and 2930 cm − 1 (b), we use the R 2850 / 2930 ratiometric image to create a binary lipid map (c). We then perform the linear least-squares spectral unmixing analysis on both C–H and fingerprint region hyperspectral SRS images of lipid molecules (d) and (e) to generate mole percentage maps of free cholesterol, saturated CE, unsaturated CE, and TAG (f)–(i). The percentage maps of free cholesterol and saturated CE are also shown with a scale extending only from 0% to 10% (for cholesterol) and 0% to 40% (for saturated CE) rather than for 0% to 100% to make more apparent the distribution of these lipids that are present in much lower relative percentages than unsaturated CEs and TAGs. Scale bar: 50 μ m .

    Journal: Journal of Biomedical Optics

    Article Title: Discrimination of lipid composition and cellular localization in human liver tissues by stimulated Raman scattering microscopy

    doi: 10.1117/1.JBO.29.1.016008

    Figure Lengend Snippet: Schematic diagram of the image analysis pipeline and representative SRS images and lipid composition maps of a liver tissue section from a patient with NASH. From the SRS images at 2850 (a) and 2930 cm − 1 (b), we use the R 2850 / 2930 ratiometric image to create a binary lipid map (c). We then perform the linear least-squares spectral unmixing analysis on both C–H and fingerprint region hyperspectral SRS images of lipid molecules (d) and (e) to generate mole percentage maps of free cholesterol, saturated CE, unsaturated CE, and TAG (f)–(i). The percentage maps of free cholesterol and saturated CE are also shown with a scale extending only from 0% to 10% (for cholesterol) and 0% to 40% (for saturated CE) rather than for 0% to 100% to make more apparent the distribution of these lipids that are present in much lower relative percentages than unsaturated CEs and TAGs. Scale bar: 50 μ m .

    Article Snippet: A nonnegative linear least-squares spectral unmixing algorithm (MATLAB Isqnonneg) was applied to both the C–H and the fingerprint region spectra for spectral unmixing of each pixel in lipid droplets.

    Techniques: