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SParSE implements one by creating a zero vector whose size is equal to the number of candidate biasing parameter sets.
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Particularly, the secret sparse basis is implemented by a reality-preserving fractional cosine transform matrix.
Recently, researchers implemented sparse component analysis (SCA) to improve the method of blind image separation [19, 20].
Multiple sparse priors (as implemented in SPM8) were used to estimate the cortical origin of the neuronal response during the encoding period (Friston et al. 2008).
The R package, sparcl [ 20], was then used to implement sparse k-means clustering using the squared Euclidean distance as the dissimilarity measure between objects, 20 random starts and a maximum of 20 iterations of the k-means algorithm.
The software tool SLEP[21] implements the sparse group lasso formulation using a version of the fast iterative shrinkage-thresholding algorithm (FISTA)[22].
We re-implemented the sparse CCA algorithm proposed in [12] using Matlab.
Mairal et al. [26] implement simultaneous sparse coding which combines between non-local means approach and dictionary learning.
Moreover, the proposed controllers are implemented through sparse communication networks and thus meet the plug-and-play feature of microgrid power systems.
Facing the difficulty to optimize such nonorthogonal and nonlinear transforms, we implement a sparse approximation scheme inspired from the functional architecture of the primary visual cortex.
Finite difference approximations to these derivatives can then be implemented using sparse matrices, thus removing the need to store and manipulate large full matrices.
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