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leastsquares method  (MathWorks Inc)


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    MathWorks Inc leastsquares method
    Leastsquares Method, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2340 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/least-square+algorithm+matlab/Database+Toolbox/pm35262283-67-18-28
    Average 96 stars, based on 2340 article reviews
    leastsquares method - by Bioz Stars, 2026-09
    96/100 stars

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    Related Articles

    other:

    Article Title: During natural vision, semantic novelty modulates fixation-related processing in primate cortex
    Article Snippet: In the human intracranial dataset, the electrode arrays each contained multiple contacts, which were identified using the iELVis MATLAB toolbox ( ).

    Article Title: From statistics to deep learning in single-molecule fluorescence resonance energy transfer analysis.
    Article Snippet: MASH-FRET [9,26], a MATLAB-based toolbox, uses the BOBA-FRET’s analysis and simulation framework, while adding workflows for molecule localisation and dynamic characterisation. iSMS [27] and SMART [28] offer graphical interfaces for data analysis and visualisation, and enhance standard HMM by incorporating VB and the Bayesian Information Criterion (BIC) while estimating the number of states.

    Software:

    Article Title: Alpha‐adrenergic mediated changes in blood pressure variability after hypoxia‐ischaemia in preterm fetal sheep
    Article Snippet: .. For beat-to-beat BPV analysis, systolic arterial blood pressure peak amplitudes were extracted using LabVIEW software and imported into a customised physiological data analysis toolbox using MATLAB (MATLAB 2023A; The MathWorks, Inc., Natick, MA, USA) to calculate features of beat-to-beat variability. ..

    Clinical Proteomics:

    Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
    Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4)58 Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

    Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
    Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4) Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

    Gentle:

    Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
    Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4)58 Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

    Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
    Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4) Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

    Generated:

    Article Title: Opposing cortical forces: Alpha slowing and sensorimotor mu acceleration during motor-related BCI training.
    Article Snippet: .. Topoplots were generated using the MATLAB toolbox from Víctor Martínez-Cagigal (2025): Topographic EEG/MEG plot (https://www.mathworks.com/matlabcentral/fileexchange/72729-topographic-eeg-meg-plot). https://doi.org/10.1371/journal.pcbi.1014112.g003 PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1014112 April 1, 2026 8 / 22 showing a positive association with posterior alpha frequency acceleration with effects ranging from negligible to moderate depending on dataset. ..

    Functional Assay:

    Article Title: Fronto-Cerebellar Connectivity Disruptions and Functional Reorganization in Friedreich's Ataxia: A Structural and Resting-State fMRI Study.
    Article Snippet: .. For functional data, grouplevel analyses were performed using the CONN toolbox in MATLAB (v.R2022a) (Nieto-Castanon and Whitfield-Gabrieli, 2022). ..



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    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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    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: