Abstract
Three-mode PCA is very computer demanding. It requires a large amount of storage space and many floating point operations (FLOPS). By using three-mode B-spline compression of three-mode data arrays, the original data array can be replaced by a smaller coefficient array. Three-mode principal component analysis (PCA) is then performed on the much smaller coefficient array instead of on the original array. For the compression approach to be efficient the three-mode data array is assumed to be well approximated by smooth functions. The smoothness affects the dimensions of the coefficient array. It is always possible to approximate the data to any precision but the reward in reduced computation time and storage is lost when the dimensions of the coefficient array approach the dimensions of the original array.
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