Sparse-firing regularization methods for spiking neural networks with time-to-first spike coding.
Yusuke SakemiKakei YamamotoTakeo HosomiKazuyuki AiharaPublished in: CoRR (2023)
Keyphrases
- regularization methods
- spiking neural networks
- synaptic weights
- spiking neurons
- edge preserving
- biologically inspired
- total variation
- biologically plausible
- neural network
- regularization method
- inverse problems
- artificial neural networks
- feed forward
- neural network model
- regularization parameter
- iterative methods
- learning rules
- hodgkin huxley
- motor control
- high dimensional
- image restoration
- higher order
- learning algorithm
- input pattern
- global optimization
- image enhancement
- denoising
- image sequences