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From the simulation results, it can be demonstrated that the MDC matrix can largely compress neural signals and also have a small reconstruction error.
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In contrast, in [12] it is theoretically shown that (eta<0.5) only requires increasingly larger data sets for achieving small reconstruction errors.
The small reconstruction errors obtained with Carmona's method seems to indicate that the two ridges, supposed to be FWL and FWH, are enough to account for almost 80% of the total energy of EHG bursts.
After a set of overcomplete ICA basis functions are learned from the densely sampled 3D patches from training videos for each action, a test video is classified as the class whose basis functions can reconstruct the sampled 3D patches from the test video with the smallest reconstruction error.
The optimal state is the state with smallest reconstruction error.
However, the IJSR model slightly outperforms the JSR model with a smaller reconstruction error.
The results from the two case studies demonstrate that AAELM achieve a smaller reconstruction error, shorter detection delay, lower spillover and a higher distinguishability compared to AAKR and PCA on the evaluated datasets.
Figure 8 shows the situation that the JSR model infers a wrong result while the IJSR model obtains the right predication of the class label with a slightly smaller reconstruction error on T72 than on BMP2.
Demaret et al. [11, 12] have introduced the greedy-point removal (GPR) scheme that first constructs a triangular mesh using all the image points and then removes the sample points that yield smallest reconstruction error repeatedly.
We found that this approach has the smallest reconstruction error (the objective function of NMF) and largest sparsity.
Further, randomly initialized solutions tend to have a smaller reconstruction error if their H matrix is more similar to the NNDSVD solution (Additional file 2: Figure S1).
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