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non-linear optimiser fmincon  (MathWorks Inc)


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    MathWorks Inc non-linear optimiser fmincon
    Non Linear Optimiser Fmincon, 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+optimiser/pm38985096-481-8-5
    Average 90 stars, based on 1 article reviews
    non-linear optimiser fmincon - by Bioz Stars, 2026-11
    90/100 stars

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    Article Title: How to design optimal brain stimulation to modulate phase-amplitude coupling?
    Article Snippet: Local optimisations are performed in Matlab using the non-linear optimiser fmincon based on the interior-point algorithm [66], under the constraint that the energy of the waveform (given by ∑Nu j [a 2 j + b 2 j ]/2) is kept within a small tolerance (ε= 0.1) of the target waveform energy Ξ.

    Article Title: Model Calibration for a Rigid Hexapod-Based End-Effector with Integrated Force Sensors
    Article Snippet: Optimisation calculations, performed using model 9 for the criteria (A, D, K, N) of , different orders (1–7) and different solvers (‘interior-point’, ‘active-set’ and ‘sqp’ of Matlab R2019a (The Mathworks Inc., Natick, MA, USA) fmincon optimiser for constrained non-linear minimisation), show the best results using the ‘active-set’ solver, D- or N-optimal criterion and third to fifth order trajectories, such as those presented in right.

    Article Title: Optimisation of a converging-diverging nozzle for the wet-to-dry expansion of the siloxane MM
    Article Snippet: A non-linear constrained optimisation is setup using the gradient-based fmincon optimiser available in MATLAB.

    Article Title: Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities
    Article Snippet: To estimate the MAPs of model parameters conditioned on the MLM, we use the inbuilt fmincon optimiser in MATLAB, using starting positions of the parameters as those identified at the minimum negative log of the posterior.



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    Optimisation routine.

    Journal: Frontiers in Bioengineering and Biotechnology

    Article Title: Identification of a lumped-parameter model of the intervertebral joint from experimental data

    doi: 10.3389/fbioe.2024.1304334

    Figure Lengend Snippet: Optimisation routine.

    Article Snippet: Using an interior-point optimisation algorithm (‘fmincon’) in MatLab the rotational stiffness in flexion-extension (FE), and the translational stiffnesses in the axial and the anterior-posterior directions were optimised to minimise the following cost function (Eq.): c f = ∑ i = n w i p i − m i 2 (1) The cost function was the sum of the weighted squared absolute error between predicted ( p i ) and measured ( m i ) motion in n DoF (where n = 8, anterior-posterior, axial, right-left translation, and flexion-extension for L2 and L3).

    Techniques: