Review



coder tm  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 95
      Buy from Supplier

    Structured Review

    MathWorks Inc coder tm
    Coder Tm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 169 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+global+optimisation+toolbox/MATLAB+Coder/pmc10474606-121-15-14
    Average 95 stars, based on 169 article reviews
    coder tm - by Bioz Stars, 2026-09
    95/100 stars

    Images

    Related Articles

    other:

    Article Title: Towards the transformation of MATLAB models into FPGA-Based hardware accelerators
    Article Snippet: The forward pass of the reference model is independently reimplemented in MATLAB scripts and in manually optimized HLS-based C + + code, while the HDL Coder workflow is used as a comparative baseline.

    Article Title: Method and system for measuring, predicting and optimizing human alertness
    Article Snippet: The algorithms for group-average and individualized predictions were written in MATLAB, translated to C with MATLAB Coder, and then compiled into a native library.

    Article Title: Predictive temperature control of electric two wheeler hub motor using gradient aware neural regulation with degradation tracking and fault tolerant multi condition torque adaptation.
    Article Snippet: All artificial neural network (ANN) models were converted into fixed-point C code using MATLAB Coder and Embedded Coder toolchains.

    Article Title: Real-time Covid-19 diagnosis on embedded IoT platforms
    Article Snippet: The trained model was converted into an embedded-compatible format using MATLAB Coder and GPU Coder, generating CUDA-accelerated code optimized for the GPU resources available on the NVIDIA Jetson platform.

    Article Title: Towards the transformation of MATLAB models into FPGA-Based hardware accelerators.
    Article Snippet: The forward pass of the reference model is independently reimplemented in MATLAB scripts and in manually optimized HLS-based C++ code, while the HDL Coder workflow is used as a comparative baseline.

    Software:

    Article Title: Towards the transformation of MATLAB models into FPGA-Based hardware accelerators.
    Article Snippet: AMD’s Vitis Model Composer, integrated as a Simulink add-on, supports rapid prototyping of FPGA-oriented systems [12]. .. Similarly, MATLAB Coder and Hardware Description Language (HDL) Coder facilitate the conversion of algorithms developed in MATLAB into C/C++ or HDL representations, thereby bridging software-oriented models with hardware-oriented implementations [13]. ..

    Article Title: Towards the transformation of MATLAB models into FPGA-Based hardware accelerators
    Article Snippet: AMD’s Vitis Model Composer, integrated as a Simulink add-on, supports rapid prototyping of FPGA-oriented systems . .. Similarly, MATLAB Coder and Hardware Description Language (HDL) Coder facilitate the conversion of algorithms developed in MATLAB into C/C + + or HDL representations, thereby bridging software-oriented models with hardware-oriented implementations . ..

    Blocking Assay:

    Article Title: Predictive temperature control of electric two wheeler hub motor using gradient aware neural regulation with degradation tracking and fault tolerant multi condition torque adaptation.
    Article Snippet: .. Once trained, the ANN model is exported as a lightweight C-code block using MATLAB CoderTM for embedded deployment. ..



    Similar Products

    matlab global optimisation toolbox  (MathWorks Inc)
    96
    MathWorks Inc matlab global optimisation toolbox
    Matlab Global Optimisation Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab+global+optimisation+toolbox/Database+Toolbox/pm39832857-164-0-0
    Average 96 stars, based on 1 article reviews
    matlab global optimisation toolbox - by Bioz Stars, 2026-09
    96/100 stars
    		  Buy from Supplier
    simulated annealing algorithm within matlab's global optimisation toolbox  (MathWorks Inc)
    90
    MathWorks Inc simulated annealing algorithm within matlab's global optimisation toolbox
    Simulated Annealing Algorithm Within Matlab's Global Optimisation Toolbox, 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/matlab+global+optimisation+toolbox/pm37578984-160-48-47
    Average 90 stars, based on 1 article reviews
    simulated annealing algorithm within matlab's global optimisation toolbox - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    oqnlp (or global search in its implementation in matlab's global optimisation toolbox)  (MathWorks Inc)
    90
    MathWorks Inc oqnlp (or global search in its implementation in matlab's global optimisation toolbox)
    Basic study: convergence of the objective function f O 2 for Bayesian <t>optimisation</t> and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations starting from 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)
    Oqnlp (Or Global Search In Its Implementation In Matlab's Global Optimisation Toolbox), 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/matlab+global+optimisation+toolbox/pmc09285944-275-11-23
    Average 90 stars, based on 1 article reviews
    oqnlp (or global search in its implementation in matlab's global optimisation toolbox) - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    genetic algorithm of the global optimisation toolbox of matlab r2016  (MathWorks Inc)
    90
    MathWorks Inc genetic algorithm of the global optimisation toolbox of matlab r2016
    Basic study: convergence of the objective function f O 2 for Bayesian <t>optimisation</t> and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations starting from 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)
    Genetic Algorithm Of The Global Optimisation Toolbox Of Matlab R2016, 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/matlab+global+optimisation+toolbox/10__1080_slash_16168658__2021__1938868-150-14-13
    Average 90 stars, based on 1 article reviews
    genetic algorithm of the global optimisation toolbox of matlab r2016 - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    genetic algorithm functions matlab global optimisation toolbox  (MathWorks Inc)
    90
    MathWorks Inc genetic algorithm functions matlab global optimisation toolbox
    Basic study: convergence of the objective function f O 2 for Bayesian <t>optimisation</t> and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations starting from 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)
    Genetic Algorithm Functions Matlab Global Optimisation Toolbox, 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/matlab+global+optimisation+toolbox/pmc05814443__41467_2018_2898_MOESM1_ESM-242-12-11
    Average 90 stars, based on 1 article reviews
    genetic algorithm functions matlab global optimisation toolbox - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    global optimisation toolbox (i.e. ga) of matlab® version r2015b  (MathWorks Inc)
    90
    MathWorks Inc global optimisation toolbox (i.e. ga) of matlab® version r2015b
    Basic study: convergence of the objective function f O 2 for Bayesian <t>optimisation</t> and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations starting from 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)
    Global Optimisation Toolbox (I.E. Ga) Of Matlab® Version R2015b, 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/matlab+global+optimisation+toolbox/10__1080_slash_15732479__2016__1198405-138-14-16
    Average 90 stars, based on 1 article reviews
    global optimisation toolbox (i.e. ga) of matlab® version r2015b - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Basic study: convergence of the objective function f O 2 for Bayesian optimisation and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations starting from 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Basic study: convergence of the objective function f O 2 for Bayesian optimisation and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations starting from 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Basic study: convergence of the objective function for Bayesian optimisation and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Basic study: convergence of the objective function for Bayesian optimisation and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Basic study: stretch‐stress curves for four LV geometries (HV A, HV B, HV C, HV D). Left: responses to stretches along the myocyte direction f 0 , right: responses to stretches along the sheet direction s 0 (see (2)). Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Basic study: stretch‐stress curves for four LV geometries (HV A, HV B, HV C, HV D). Left: responses to stretches along the myocyte direction f 0 , right: responses to stretches along the sheet direction s 0 (see (2)). Bayesian optimisation with a target surrogate (target) and a partial error surrogate (partial) together with the old version of the HGO algorithm (HGO old)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Klotz‐curve study: convergence of the objective function f O 2 , Klotz for Bayesian optimisation and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations after 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.), three independent runs (v1, v2, v3) in each version, together with the new version of the HGO algorithm (HGO new). For HGO, the Klotz curve error was computed using the forward simulator (not the emulator)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Klotz‐curve study: convergence of the objective function f O 2 , Klotz for Bayesian optimisation and the original HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D). Horizontal axis: Bayesian optimisation iterations after 40 iterations for the initial design. Vertical axis: best value of the objective function f O 2 recorded so far. Black dot and horizontal dashed line: the final value of the objective function f O 2 for the HGO algorithm and the associated number of iterations. Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.), three independent runs (v1, v2, v3) in each version, together with the new version of the HGO algorithm (HGO new). For HGO, the Klotz curve error was computed using the forward simulator (not the emulator)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Klotz‐curve study: convergence of the objective function for Bayesian optimisation and the updated HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Klotz‐curve study: convergence of the objective function for Bayesian optimisation and the updated HGO algorithm for four LV geometries (HV A, HV B, HV C, HV D)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Klotz‐curve study: stretch‐stress curves for four LV geometries (HV A, HV B, HV C, HV D). Left: responses to stretches along the myocyte direction f 0 , right: responses to stretches along the sheet direction s 0 (see (2)). Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.), three independent runs (v1, v2, v3) in each version

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Klotz‐curve study: stretch‐stress curves for four LV geometries (HV A, HV B, HV C, HV D). Left: responses to stretches along the myocyte direction f 0 , right: responses to stretches along the sheet direction s 0 (see (2)). Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.), three independent runs (v1, v2, v3) in each version

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Basic setting: final optimised values of the eight parameters of the HO law for Bayesian optimisation and the original HGO algorithm (HGO old) for four different LV geometries (HV A, HV B, HV C, HV D), Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Basic setting: final optimised values of the eight parameters of the HO law for Bayesian optimisation and the original HGO algorithm (HGO old) for four different LV geometries (HV A, HV B, HV C, HV D), Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Klotz‐curve study: final optimised values of the parameters of the HO law for Bayesian optimisation and the updated HGO algorithm for four LV different geometries (HV A, HV B, HV C, HV D)

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Klotz‐curve study: final optimised values of the parameters of the HO law for Bayesian optimisation and the updated HGO algorithm for four LV different geometries (HV A, HV B, HV C, HV D)

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques:

    Klotz study: decomposition of the incumbent trajectories from Figure based on f O 2 , Klotz from (11) into f O 2 from (6) (top) and the Klotz component (bottom). Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.), three independent runs (v1, v2, v3) in each version

    Journal: International Journal for Numerical Methods in Biomedical Engineering

    Article Title: Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

    doi: 10.1002/cnm.3593

    Figure Lengend Snippet: Klotz study: decomposition of the incumbent trajectories from Figure based on f O 2 , Klotz from (11) into f O 2 from (6) (top) and the Klotz component (bottom). Bayesian optimisation with a target surrogate (targ.) and a partial error surrogate (part.), three independent runs (v1, v2, v3) in each version

    Article Snippet: For these reasons we use a different approach based on a global optimisation algorithm called OQNLP (or Global Search in its implementation in MATLAB's Global Optimisation toolbox that we use), which led to very stable results.

    Techniques: