Robustness to training disturbances in SpikeProp Learning
Stability is a key issue during spiking neural network training using SpikeProp. The inherent nonlinearity of Spiking Neuron means that the learning manifold changes abruptly; therefore, we need to carefully choose the learning steps at every instance. Other sources of instability are the external d...
Saved in:
Main Authors: | Shrestha, Sumit Bam, Song, Qing |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139881 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Surge in SpikeProp algorithm
by: Zhang, Zhengyang
Published: (2014) -
Supervised learning in multilayer spiking neural network
by: Shrestha, Sumit Bam
Published: (2017) -
Capacity of rate adaptive MQAM systems in the presence of channel estimation errors under BER constraint
by: Mo, R., et al.
Published: (2014) -
Inductive robust principal component analysis
by: Bao, B.-K., et al.
Published: (2014) -
Automatic Spike sorting and robust power line interference cancellation for neural signal processing
by: MOHAMMADREZA KESHTKARAN
Published: (2014)