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singular value decomposition methods  (MathWorks Inc)


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    MathWorks Inc singular value decomposition methods
    Singular Value Decomposition Methods, 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/singular+value+decomposition+method/pmc11954597-95-10-7
    Average 90 stars, based on 1 article reviews
    singular value decomposition methods - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Performance of Orbitrap mass analyzer at various space charge and non-ideal field conditions: simulation approach.
    Article Snippet: The MATLAB implementation of the singular value decomposition method was used for this.

    Article Title: Role of adenine in thymine-dimer repair by reduced flavin-adenine dinucleotide.
    Article Snippet: The noise in the data was reduced using a singular value decomposition (SVD) method (Matlab 7.1).

    Article Title: Correlation ranking and stepwise regression procedures in principal components artificial neural networks modeling with application to predict toxic activity and human serum albumin binding affinity
    Article Snippet: Abbreviations: ANN, artificial neural networks; CR, co correlation ranking principal components artificial neu correlation ranking principal components artificial ne combined approach; CR-PC-ANN(I), stepwise regression neural networks based on the individual approach; FE, selection; HOMO, highest occupied molecular orbital; H IC50, logarithm of half maximal inhibitory concentrat cross validation; log K'hsa, logarithm of HSA binding affin molecular orbital; MLR, multiple linear regression; PC, p principal components artificial neural networks; PCA, p PCA(C), principal components analysis based on the principal components analysis based on the individ component regression; R, coefficient of determin coefficient of determination; RMSE, root mean squa correlation coefficient between the predicted and a regression; SR-PC-ANN, stepwise regression principal networks; SR-PC-ANN(C), stepwise regression principa networks based on the combined approach; SR-PC principal components artificial neural networks based SVD, singular value decomposition.. ⁎ Tel./fax: +972 2790413.. E-mail address: deeb2000il@yahoo.com.

    Article Title: Principal component analysis of PiB distribution in Parkinson and Alzheimer diseases
    Article Snippet: The singular value decomposition method, denoted in MATLAB by sdv ( X , “econ”) (for N > M ), decomposes the data into 3 matrices ( U, S, V ): where the M × M matrix U is the eigenvector matrix, S is a real M × M diagonal matrix containing the singular values (square root of the eigenvalues), and V is a N × M matrix.

    Article Title: Light-triggered proton and electron transfer in flavin cofactors.
    Article Snippet: Then, the time arrays from the transient absorption data were chirp-corrected by subtracting the value of zero-time at every wavelength. (ii) Noise reduction: The noise in the data was reduced using a singular value decomposition (SVD) method (Matlab 7.1).

    Article Title: Comparative study of composition of methanolic extracts of the paratoid gland secretions (PGS) of Rhinella jimi (cururu toad) from northeastern Brazil: Gender, seasonality and geographic occurrence.
    Article Snippet: Principal component analysis was performed using singular value decomposition method with the MATLAB software (MathWorks, Inc, Natick, MA, USA).



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    Image Search Results


    The used thresholds for the calculation of the core and penumbra volumes for the different perfusion analysis methods

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: The used thresholds for the calculation of the core and penumbra volumes for the different perfusion analysis methods

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques:

    Mean perfusion parameters with 95% confidence interval for grey matter for bSVD, ISP, and NLR. The values that are significantly different from the 1 s acquisition interval (reference) are filled and marked with an asterisk. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: Mean perfusion parameters with 95% confidence interval for grey matter for bSVD, ISP, and NLR. The values that are significantly different from the 1 s acquisition interval (reference) are filled and marked with an asterisk. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques:

    Mean perfusion parameters with 95% confidence interval for white matter for bSVD, ISP and NLR. The values that are significantly different from the 1 s acquisition interval (reference) are filled and marked with an asterisk. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: Mean perfusion parameters with 95% confidence interval for white matter for bSVD, ISP and NLR. The values that are significantly different from the 1 s acquisition interval (reference) are filled and marked with an asterisk. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques:

    An example of calibrated CBF maps generated using bSVD, ISP, and NLR as a function of acquisition interval. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: An example of calibrated CBF maps generated using bSVD, ISP, and NLR as a function of acquisition interval. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques: Generated

    An example of calibrated CBV maps generated using bSVD, ISP, and NLR as a function of acquisition interval. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: An example of calibrated CBV maps generated using bSVD, ISP, and NLR as a function of acquisition interval. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques: Generated

    An example of calibrated MTT maps generated using bSVD, ISP, and NLR as a function of acquisition interval. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: An example of calibrated MTT maps generated using bSVD, ISP, and NLR as a function of acquisition interval. [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques: Generated

    Summary maps of bSVD, ISP, and NLR as a function of acquisition interval. The infarct core is labeled red, the penumbra labeled green. This is the same patient as shown in Figs. , , . [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Journal: Medical Physics

    Article Title: Effect of prolonged acquisition intervals for CT‐perfusion analysis methods in patients with ischemic stroke

    doi: 10.1002/mp.13559

    Figure Lengend Snippet: Summary maps of bSVD, ISP, and NLR as a function of acquisition interval. The infarct core is labeled red, the penumbra labeled green. This is the same patient as shown in Figs. , , . [Color figure can be viewed at http://wileyonlinelibrary.com ]

    Article Snippet: A commercial block‐circulant singular value decomposition (bSVD) based method (ISP; Philips Healthcare), a non‐commercial bSVD method, and a non‐linear regression (NLR) model‐based method were evaluated.

    Techniques: Labeling