ccaObjective.m create_scanoncorr_example.m crossValidateScanoncorr.m deflate.m optimiseScanoncorrParameters.m projectL1.m scanoncorr.m scanoncorrFromInit.m scanoncorr_example.mat scanoncorrperforms sparse canonical correlation analysis in MATLAB. The algorithm is based on the alternating projected gradient...
We developed structured sparse multiset canonical correlation analysis (ssmCCA) to perform EEG-fNIRS data fusion. MCCA is a generalization of CCA to more than two sets of variables and is commonly used in medical multimodal data fusion. However, mCCA suffers from multi-collinearity, high ...
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Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA Magn. Reson. Imag., 28 (8) (2010), pp. 1095-1103 Oct 1 View PDFView articleView in ScopusGoogle Scholar Ogawa et al., 1992 S. Ogawa, D.W. Tank, R. Menon, J.M. Ellermann,...
MATLAB (R27:0O14uat)pputlatform. Assuming the clean image x, we construct a measurement matrix Φ using the "Spread Spectrum" op4.ePraetrofor r[m35a]n, csoe AthneamlyesaissuarnedmDenistciumssaigoenshows: y = Φx + n, where n denotes the additive noise. Since tWhee wfirasvtecloet...
MATLAB software was used to build it. Table 3 shows the dynamic models and estimator specification. To overcome the truncation error in the calculation of high-order term geopotential perturbation (up to 60 × 60), the recursive computation of Legendre polynomials technique was applied [38]. We...
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All of these methods are implemented in MATLAB 2015a on a PC with Core i7 2.4 GHz CPU and 12GB RAM. Following [20,24], the parameters in each method, such as the number of K-nearest neighbors in LLS, the dimensionality of latent space in PPCA, are tuned to give optimal performance....
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MATLAB R2014a on a laptop that is equipped with eight Intel Core i7-7700HQ CPU with 16 GB RAM, is used to implement the algorithms. The proposed HyDeSpDLS is compared with seven state-of-the-art HSI denoisers in both synthetic and real experiments,: BM3D, BM4D, PCA + BM4D, LRMR, ...