Experimental Evaluation of Computational Complexity for Different Neural Network Equalizers in Optical Communications.
Pedro J. FreireYevhenii OsadchukAntonio NapoliBernhard SpinnlerWolfgang SchairerNelson CostaJaroslaw E. PrilepskySergei K. TuritsynPublished in: CoRR (2021)
Keyphrases
- experimental evaluation
- neural network
- computational complexity
- artificial neural networks
- back propagation
- np complete
- neural network model
- activation function
- genetic algorithm
- special case
- pattern recognition
- high computational complexity
- bp neural network
- low complexity
- communication systems
- multilayer perceptron
- neural network is trained
- synthetic and real datasets
- feed forward
- network architecture
- backpropagation neural network
- fiber optic
- decision problems
- computational efficiency
- self organizing maps
- fault diagnosis
- computationally efficient
- fuzzy logic
- np hard
- atmospheric turbulence
- learning vector quantization
- fermentation process
- multi layer perceptron
- training algorithm
- training process
- multi layer
- neural nets
- communication networks
- data sets
- radial basis function
- rate distortion
- support vector machine