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The effect of matrix normalization on the speed up ratio of face detection is discussed.

The effect of matrix normalization on the speed up ratio of pattern detection is discussed.

Original data matrix normalization.

40068_2014_31_MOESM1_ESM.doc Additional file 1: R script for matrix normalization.

With this matrix normalization, the channel attenuation is reflected in the SNR, allowing the influence of the channel correlation properties on the channel capacity to become visible.

As each secondary data source leads to a different kernel matrix, normalization is required to make them comparable.

Simulation results show that local sub-matrix normalization through weight normalization is faster than sub-matrix normalization in the spatial domain.

Moreover, the problem of local sub-matrix normalization in the frequency domain is solved.

For real-value matrices, normalization and discretization procedures are applied.

It is a reasonable assumption that the noise level is therefore influenced to a large extent by the matrix layer, and consequently, a normalization on the noise can remove the influence of the matrix layer to some extent.

The stacked barplots were generated on the count matrix after normalization for source-triplet frequency by discarding the context information and summing all counts by their associated mutation type (e.g., C > A).