Estimation of the influence of spiking neural network parameters on classification accuracy using a genetic algorithm.
Aleksandr SboevAlexey SerenkoRoman B. RybkaDanila VlasovAndrey FilchenkovPublished in: BICA (2018)
Keyphrases
- network parameters
- genetic algorithm
- classification accuracy
- bio inspired
- spike trains
- neuron model
- neural network
- spiking neural networks
- biologically plausible
- hebbian learning
- network size
- spiking neurons
- learning rules
- single neuron
- conditional probabilities
- multi objective
- rbf neural network
- network architecture
- artificial neural networks
- basal ganglia
- feature selection
- feed forward
- biologically inspired
- support vector
- evolutionary algorithm
- training set
- feature space
- training data
- machine learning
- metaheuristic
- simulated annealing
- support vector machine