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cvx matlab package  (MathWorks Inc)


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    MathWorks Inc cvx matlab package
    Summary of tES optimization methods.
    Cvx Matlab Package, 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/result/cvx matlab package/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    cvx matlab package - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans"

    Article Title: Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans

    Journal: Journal of Clinical Medicine

    doi: 10.3390/jcm13113084

    Summary of tES optimization methods.
    Figure Legend Snippet: Summary of tES optimization methods.

    Techniques Used:



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    Image Search Results


    Summary of tES optimization methods.

    Journal: Journal of Clinical Medicine

    Article Title: Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans

    doi: 10.3390/jcm13113084

    Figure Lengend Snippet: Summary of tES optimization methods.

    Article Snippet: [ ] , Guler et al., 2016 , Directional Maximization , ・Max total current ・Max per electrode current ・Max non-target energy (focality) , Convex , CVX Matlab package [ ] , Evolution of [ ] (P5) (more constraints) .

    Techniques:

    List of algorithm implementations in different pipelines. For a lot of steps, different algorithm implementation can be chosen by the user based on features of the data. In such cases, we only list the default and most commonly used algorithms here.

    Journal: eLife

    Article Title: Minian, an open-source miniscope analysis pipeline

    doi: 10.7554/eLife.70661

    Figure Lengend Snippet: List of algorithm implementations in different pipelines. For a lot of steps, different algorithm implementation can be chosen by the user based on features of the data. In such cases, we only list the default and most commonly used algorithms here.

    Article Snippet: Spatial and temporal updates , CNMF with CVXPY as deconvolution backend , CNMF-E with Oasis as deconvolution backend , CNMF with CVX MATLAB package as deconvolution backend , Noise cutoff frequency Expected size of neurons Sparse penalty.

    Techniques: