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MathWorks Inc s-parameter data
S Parameter Data, 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/s+parameter+data/10__3390_slash_electronics8121447-134-7-27
Average 90 stars, based on 1 article reviews

s-parameter data - by Bioz Stars, 2026-11

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Article Title: Fractional-order stochastic delayed neural networks with impulses: mean square finite-time contractive synchronization
Article Snippet: .. Based on these parameter values, the subsequent feasibility solution can be derived using the MATLAB LMI Toolbox: Algorithm LMI-Based controller design. .. Following the aforementioned LMI-based algorithm, the feasibility solution corresponding to the selected parameter values can be obtained using the MATLAB LMI Toolbox: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{aligned} \mathscr {P}=\begin{bmatrix} 0.0104 & -0.0176 \\ -0.0176 & 0.2088 \end{bmatrix}, \mathscr {M}=\begin{bmatrix} 1.1201 & 0 \\ 0 & 1.1201 \end{bmatrix}, \mathscr {W}=\begin{bmatrix} 1.2063 & 0 \\ 0 & 1.2063 \end{bmatrix}, G=\begin{bmatrix} 0.1584 & 0.0135 \\ 0.0135 & 0.0364 \end{bmatrix}, \end{aligned}$$\end{document} and the control gain K is obtained as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$K=\begin{bmatrix} 17.9387 & 1.8622 \\ 1.5788 & 0.3316 \end{bmatrix}$$\end{document} .

Article Title: Fractional-order stochastic delayed neural networks with impulses: mean square finite-time contractive synchronization.
Article Snippet: .. Based on these parameter values, the subsequent feasibility solution can be derived using the MATLAB LMI Toolbox: Algorithm: LMI-Based Controller Design 1. ..

other:

Article Title: Filling the gap: modelling sorption isotherms between hygroscopic and water-saturated conditions based on microscopic characterisation of softwood anatomy
Article Snippet: Values for each parameter were randomly picked from each of the normal distributions using the function normrnd in MATLAB (MATLAB R2016b/R2022a, The Mathworks Inc., Natick, MA, USA).

Article Title: Trade-off between flux efficiency and metabolic control shapes enzyme allocation.
Article Snippet: As the whole procedure computes pathway flux J from kcat ;KS;KP;K;E; Sin1⁄2 ; 1⁄2Sout , the pathway flux J can also be written as a function of these parameters and concentrations: J 1⁄4 Jðkcat ;KS;KP;K ;E; Sin1⁄2 ; 1⁄2Sout Þ Optimal enzyme allocation profile maximizing flux efficiency under a given parameter set was computed using the MATLAB constrained optimization solver fmincon[] to maximize the pathway flux with the upper bound of total enzyme abundance set to 1: max E Jðkcat ;KS;KP;K ;E; Sin1⁄2 ; 1⁄2Sout Þ s:t: 0 1⁄2Ei 1Pn i1⁄41 Ei1⁄2 1

Control:

Article Title: Fractional-order stochastic delayed neural networks with impulses: mean square finite-time contractive synchronization.
Article Snippet: .. Following the aforementioned LMI-based algorithm, the feasibility solution corresponding to the selected parameter values can be obtained using the MATLAB LMI Toolbox: P = [ 0.0104 −0.0176 −0.0176 0.2088 ] , M = [ 1.1201 0 0 1.1201 ] , W = [ 1.2063 0 0 1.2063 ] , G = [ 0.1584 0.0135 0.0135 0.0364 ] , and the control gain K is obtained as K = [ 17.9387 1.8622 1.5788 0.3316 ] . ..

Article Title: Fractional-order stochastic delayed neural networks with impulses: mean square finite-time contractive synchronization
Article Snippet: Based on these parameter values, the subsequent feasibility solution can be derived using the MATLAB LMI Toolbox: Algorithm LMI-Based controller design. .. Following the aforementioned LMI-based algorithm, the feasibility solution corresponding to the selected parameter values can be obtained using the MATLAB LMI Toolbox: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{aligned} \mathscr {P}=\begin{bmatrix} 0.0104 & -0.0176 \\ -0.0176 & 0.2088 \end{bmatrix}, \mathscr {M}=\begin{bmatrix} 1.1201 & 0 \\ 0 & 1.1201 \end{bmatrix}, \mathscr {W}=\begin{bmatrix} 1.2063 & 0 \\ 0 & 1.2063 \end{bmatrix}, G=\begin{bmatrix} 0.1584 & 0.0135 \\ 0.0135 & 0.0364 \end{bmatrix}, \end{aligned}$$\end{document} and the control gain K is obtained as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$K=\begin{bmatrix} 17.9387 & 1.8622 \\ 1.5788 & 0.3316 \end{bmatrix}$$\end{document} . ..

Software:

Article Title: Developing a novel reference region for [ 18 F]PI-2620-PET imaging to facilitate the assessment of 4-repeat tauopathies.
Article Snippet: .. MATLAB version R2023b (Statistical Parameter Mapping Software, The MathWorks Inc., Portola Valley, United States) and R Version 4.4.1 were used for statistical testing [46]. ..

Selection:

Article Title: Towards energy-efficient joint relay selection and resource allocation for D2D communication using hybrid heuristic-based deep learning.
Article Snippet: .. When considering the without relay-based analysis, the suggested mechanism’s network capacity is enhanced by 4.76% Parameter Description Simulation tool MATLAB R2020a Number of simulation runs 30 Random seed 42 HMRFCO population size 10 HMRFCO max iterations 250 Chromosome length 3(sun-channel selection, power allocation, relay index) HMRFCO convergence threshold 1e−5 AResGRU optimizer Adam Learning rate 0.001 Batch size 32 [5–50] Epochs 25 [5–50] Hidden layers (AResGRU) 2 GRU layers[128 and 64 neurons] [5–255] Activation function ReLU Loss function Mean square error (MSE) Evaluation metrics EE, Delay, Throughput, RMSE, MAE, Success rate Table 3. ..

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