Heterogeneous recurrent spiking neural network for spatio-temporal classification

HIGHLIGHTS

• who: Biswadeep Chakraborty from the Yale University, United States have published the paper: Heterogeneous recurrent spiking neural network for spatio-temporal classification, in the Journal: (JOURNAL)
• what: The authors propose the usage of heterogeneous LIF neurons with different membrane time constants and threshold voltages, thereby giving rise to multiple timescales. The authors explore the advantages of using heterogeneities in several hyperparameters discussed above. The authors show the temporal encoding method based on the sensory receptors receiving the difference between two time-adjacent data. Using the Eckart-Young-Mirsky theorem for low-rank approximation, the authors . . .
  

   

  

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