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. 2018 Nov 19;12:836. doi: 10.3389/fnins.2018.00836

Figure 2.

Figure 2

The details of the proposed SOM-SNN ASC framework. The sound frames are pre-processed and analyzed using mel-scaled filter banks. Then, the SOM generates discrete BMU activation sequences which are further converted into spike trains. All such spike trains form a spatiotemporal spike pattern to be classified by the SNN.