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constrained nonlinear optimization algorithm matlab's fmincon.m function  (MathWorks Inc)


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    MathWorks Inc constrained nonlinear optimization algorithm matlab's fmincon.m function
    Constrained Nonlinear Optimization Algorithm Matlab's Fmincon.M 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/fmincon%2Em+optimization+function/pmc03105161-640-27-30
    Average 90 stars, based on 1 article reviews
    constrained nonlinear optimization algorithm matlab's fmincon.m function - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Failure of self-consistency in the discrete resource model of visual working memory
    Article Snippet: Fitting was achieved by minimizing squared error using a nonlinear optimization algorithm ( fminsearch in MATLAB) with a range of initial parameter values.

    Article Title: Optimal degrees of freedom of the lower extremities for human walking and running.
    Article Snippet: A set of parameters for the STM at each frame was determined using a nonlinear optimization algorithm (fmincon in the MATLAB optimization toolbox) to minimize the sum of squares of the Euclidian distance for all pairs of the empirical and modeled data (Fig. 1)10,11.

    Article Title: Aberrant visual population receptive fields in human albinism
    Article Snippet: Using the starting positions established by the coarse search, polar angle, σ, and amplitude (sensitivity) were refined in a two-pass, coarse-to-fine fashion using an unconstrained nonlinear optimization algorithm (Matlab's fminsearch) to obtain an optimal fit to the empirical rotating wedge fMRI waveform.

    Article Title: Determination of the optimal number of linked rigid-bodies of the trunk during walking and running based on Akaike's information criterion.
    Article Snippet: A set of parameters for the STM at each frame to minimize the sum of squares of the Euclidian distance for all pairs of the empirical and modeled data were determined by using a nonlinear optimization algorithm (fmincon in the MATLAB optimization toolbox; Fig. 2).

    Article Title: Independent working memory resources for egocentric and allocentric spatial information
    Article Snippet: The model was fit to each participant’s data using maximum likelihood obtained by a nonlinear optimization algorithm ( fmincon in MATLAB).

    Article Title: Joint analysis of spikes and local field potentials using copula.
    Article Snippet: 13 14 15 16 Article history: Received 23 December 2015 Accepted 13 March 2016 Available online xxxx 17 18 19 20 21 22 23 24 25 26 27 T E D P R Recent technological advances, which allow for simultaneous recording of spikes and local field potentials (LFPs) atmultiple sites in a given cortical area or across different areas, have greatly increased our understanding of signal processing in brain circuits.. Joint analysis of simultaneously collected spike and LFP signals is an important step to explicate how the brain orchestrates information processing.. In this contribution, we present a novel statistical framework based on Gaussian copula to jointly model spikes and LFP.

    Article Title: Twist buckling of veins under torsional loading
    Article Snippet: The material constants were obtained by minimizing the error function using an optimization routine in MATLAB consisting of a combination of genetic algorithm and a constrained nonlinear optimization algorithm ( Garcia et al. 2013 ).

    Article Title: Transsaccadic integration operates independently in different feature dimensions
    Article Snippet: The probability of both responses is then given by (17) p x ^ C , y = 1 - γ p x ^ C , y ^ = y + γ p x ^ C , y ^ = 1 - y We used a nonlinear optimization algorithm ( fminsearch in MATLAB) to find parameters of the model that maximized this likelihood over all trials, for each participant separately.



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