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least-squares algorithm  (MathWorks Inc)


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    MathWorks Inc least-squares algorithm
    Least Squares 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-squares+algorithm/pmc12267651-385-30-36
    Average 90 stars, based on 1 article reviews
    least-squares algorithm - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Attosecond field emission
    Article Snippet: The reconstruction is based on a least-squares algorithm written in MATLAB, which aims at the total minimization of the difference among the experimental (Fig. and Extended Data Fig. ) and reconstructed spectrogram (Fig. and Extended Data Fig. ).

    Article Title: Deep learning-based high-resolution time inference for deciphering dynamic gene regulation from fixed embryos
    Article Snippet: Within position ranges 0.10−0.75 EL (for Bcd), 0.15−0.85 EL (for Hb), 0.20−0.85 EL (for Kr in OreR ), and 0.10−0.80 EL (for Kr in 1× bcd ), we used a least-squares algorithm (the “fit” function in MATLAB) to fit the binned data from each species to the following functions: 5 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[{{{\rm{Bcd}}}}]={c}_{1,{{{\rm{Bcd}}}}}{e}^{-x/\lambda }+{c}_{0,{{{\rm{Bcd}}}}},$$\end{document} [ Bcd ] = c 1 , Bcd e − x / λ + c 0 , Bcd , 6 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[{{{\rm{Hb}}}}]={c}_{1,{{{\rm{Hb}}}}}\frac{{e}^{-(x-{x}_{0})/d}}{{e}^{-(x-{x}_{0})/d}+1}+{c}_{0,{{{\rm{Hb}}}}},$$\end{document} [ Hb ] = c 1 , Hb e − ( x − x 0 ) / d e − ( x − x 0 ) / d + 1 + c 0 , Hb , 7 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R={r}_{1}\frac{{e}^{(x-{x}_{{{{\rm{A}}}}})/{d}_{{{{\rm{A}}}}}}}{{e}^{(x-{x}_{{{{\rm{A}}}}})/{d}_{{{{\rm{A}}}}}}+1}\cdot \frac{{e}^{-(x-{x}_{{{{\rm{P}}}}})/{d}_{{{{\rm{P}}}}}}}{{e}^{-(x-{x}_{{{{\rm{P}}}}})/{d}_{{{{\rm{P}}}}}}+1}+{r}_{0},$$\end{document} R = r 1 e ( x − x A ) / d A e ( x − x A ) / d A + 1 ⋅ e − ( x − x P ) / d P e − ( x − x P ) / d P + 1 + r 0 , where c 1,· , c 0,· , r 1 , and r 0 denote the peak and background levels of the corresponding species, respectively; λ , d , d A , and d P indicate the decay lengths of Bcd, Hb, and Kr patterns, respectively; x 0 represents the boundary position of Hb expression pattern; x A and x P denote the anterior and posterior boundary positions of Kr expression domain, respectively.

    Article Title: Neuronal Correlates of Tactile Working Memory in Prefrontal and Vibrissal Somatosensory Cortex
    Article Snippet: The coefficients w1 , w2 , and C were computed using a least-squares algorithm implemented in MATLAB.

    Article Title: Improving Stroke Treatment Using Magnetic Nanoparticle Sensors to Monitor Brain Thrombus Extraction.
    Article Snippet: The inverse cubic function was fitted using the default least-squares algorithm in MATLAB.

    Article Title: Neuronal Correlates of Tactile Working Memory in Prefrontal and Vibrissal Somatosensory Cortex
    Article Snippet: The coefficients w1, w2, and C were computed using a least-squares algorithm implemented in MATLAB.

    Article Title: Improving Stroke Treatment Using Magnetic Nanoparticle Sensors to Monitor Brain Thrombus Extraction.
    Article Snippet: The inverse cubic function was fitted using the default least-squares algorithm in MATLAB. (a) (b) Sensors 2025, 25, x FOR PEER REVIEW 14 of 17 (c) (d) Figure 13.

    Article Title: Improving Stroke Treatment Using Magnetic Nanoparticle Sensors to Monitor Brain Thrombus Extraction.
    Article Snippet: The inverse cubic function was fitted using the default least-squares algorithm in MATLAB. (a) (b) Figure 12.

    Article Title: Modularized Design and Construction of Tunable Microbial Consortia with Flexible Topologies.
    Article Snippet: Complex and fluid bacterial community compositions are critical to diversity, stability, and function.. However, quantitative and mechanistic descriptions of the dynamics of such compositions are still lacking.. Here, we develop a modularized design framework that allows for bottom-up construction and the study of synthetic bacterial consortia with different topologies.



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