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. 2015 May 22;9:51. doi: 10.3389/fncom.2015.00051

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Copyright © 2015 Schönfeld and Wiskott.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Overview of our hierarchical Slow Feature Analysis (SFA) network. SFA nodes in the lowest layer directly work on our software-generated image frames. Each node scans a predetermined receptive field that overlaps 50% with directly adjacent ones. The second layer works on the pre-processed output of the first layer. The third layer consists of a single SFA node integrating the output of all layer-2 SFA nodes. The last layer is one node performing independent component analysis (ICA) to perform sparse coding on the final SFA output.