Fluctuation-driven learning rule for continuous-time recurrent neural networks and its application to dynamical system control.
Kazuhisa WatanabeTakahiro HabaNoboru KudoTakahumi OohoriPublished in: Systems and Computers in Japan (2001)
Keyphrases
- dynamical systems
- recurrent neural networks
- learning rules
- neural network
- artificial neural networks
- nonlinear dynamics
- feed forward
- discrete event
- recurrent networks
- differential equations
- biologically inspired
- state space
- reservoir computing
- phase space
- optimal control
- nonlinear dynamical systems
- nonlinear dynamic systems
- hidden layer
- linear quadratic
- echo state networks
- dynamical behavior
- learning scheme
- control system
- learning algorithm
- control method
- predictive state representations
- decision making
- spiking neural networks
- spatio temporal
- search algorithm
- expert systems
- radial basis function
- feedforward neural networks
- control law
- dynamic programming
- fuzzy logic
- cellular automata