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singular value decomposition method  (MathWorks Inc)


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    MathWorks Inc singular value decomposition method
    Singular Value Decomposition Method, 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/pm35562061-75-6-12
    Average 90 stars, based on 1 article reviews
    singular value decomposition method - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Dual-channel pulse-dye densitometry can enable correction of fluorescent targeted and control agent plasma input function differences for quantitative paired-agent molecular imaging: a simulation study
    Article Snippet: The deconvolution operation was carried out in MATLAB using a singular value decomposition methods as described in detail previously.

    Article Title: Classification of urinary stones using near-infrared spectroscopy and chemometrics: A promising method for intraoperative application.
    Article Snippet: • Near-infrared spectroscopy was applied for quantitative analysis of urinary

    Article Title: Heterogeneous spatial tuning in the auditory pathway of the Mongolian Gerbil (Meriones unguiculatus).
    Article Snippet: Per nucleus, we normalized the RAFs to the maximum spike rate elicited by the loudest level tested and subtracted the mean across all normalized RAFs before performing a singular value decomposition (Matlab function: pca with ‘svd’ algorithm option).

    Article Title: Atypical low-frequency cortical encoding of speech identifies children with developmental dyslexia
    Article Snippet: In practice, the matrix A was estimated using Singular Value Decomposition ( svd function in MATLAB) and consists of a set of eigenvectors sorted by their eigenvalues (diagonal elements of matrix Λ ).

    Article Title: Sequential neuronal processing of number values, abstract decision, and action in the primate prefrontal cortex
    Article Snippet: The principal components of this matrix were identified by decomposing the covariance matrix C of X using singular value decomposition (as implemented by pca.m in MATLAB): C = PDPT, in which each column of P is an eigenvector of C and D is a diagonal matrix of corresponding eigenvalues.

    Article Title: Extended Operational Space Kinematics, Dynamics, and Control of Redundant Serial Robots
    Article Snippet: For a given j and base point xj ∈ Nj ⊂ X̃, define the n × m matrix Uj and an n × (n − m) matrix Vj such that Uj = G′T(yj) G′(yj) Vj = 0 VjTVj = I (10) where Vj is computed as a matrix whose columns form an orthonormal basis for the null space of G′(yj), e.g., in MATLAB, using singular value decomposition [23].

    Article Title: Comparing the performance of beamformer algorithms in estimating orientations of neural sources
    Article Snippet: The vectors were obtained by performing a Singular Value Decomposition (as implemented in MATLAB) on the MEG target leadfield as L M ( r ) = U S V ⊺ , where U ∈ R N ch × N ch , S ∈ R N ch × 3 and V = ( v t 1 , v t 2 , v r ) ∈ R 3 × 3 .

    Article Title: Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss
    Article Snippet: To align two sets of signal dynamics, U = X A and V = Y B were computed using QR factorization and singular value decomposition (MATLAB cannoncorr ), where X and Y are the matrices containing the original dynamics, A and B are the matrices containing the canonical components, and U and V are the aligned dynamics.



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