Sparse and burst spiking in artificial neural networks inspired by synaptic retrograde signaling.
Faramarz FaghihiAhmed A. MoustafaPublished in: Inf. Sci. (2017)
Keyphrases
- artificial neural networks
- feed forward
- spiking neural networks
- learning rules
- back propagation
- neuron model
- neural models
- spiking neurons
- neural network
- single neuron
- hidden layer
- feed forward neural networks
- hebbian learning
- bio inspired
- using artificial neural networks
- computational intelligence
- biologically plausible
- activation function
- sparse data
- high dimensional
- genetic algorithm ga
- recurrent neural networks
- biologically inspired
- synaptic plasticity
- visual cortex
- genetic algorithm
- application of artificial neural networks
- training algorithm
- radial basis function
- sparse representation
- spike trains
- compressed sensing
- compressive sensing
- soft computing
- sparse coding
- evolutionary artificial neural networks