Improvement of the convergence speed of a discrete-time recurrent neural network for quadratic optimization with general linear constraints.
María José Pérez-IlzarbePublished in: Neurocomputing (2014)
Keyphrases
- convergence speed
- recurrent neural networks
- linear constraints
- quadratic optimization
- convergence rate
- differential evolution
- neural network
- global convergence
- particle swarm optimization
- feed forward
- complex valued
- pso algorithm
- steady state error
- hidden layer
- learning rate
- special case
- machine learning
- back propagation
- evolutionary algorithm
- artificial neural networks