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. Author manuscript; available in PMC: 2020 Jun 1.
Published in final edited form as: IEEE Trans Big Data. 2018 Mar 6;5(2):109–119. doi: 10.1109/TBDATA.2018.2811508

Fig. 5.

Fig. 5.

Illustration of the D-r1DL framework. (a) Running example showing the input data S (one volume from the 4-D volumetric matrix), learned vector v (3-D volumetric matrix as a vector) and vector u (time series). (b) Algorithmic pipeline of r1DL. Red arrow shows the updating loop for learning each [u, v], blue arrow shows the updating loop for deflation of S and learning next dictionary. (c) Parallelization steps for the three operations from (b).